Search

Your search keyword '"Noel, C"' showing total 4,789 results
Start Over Author "Noel, C"

Refine your results

more »

more »

more »

more »

more »

more »
4,789 results on '"Noel, C"'

1. MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging

Author

Codella, Noel C. F., Jin, Ying, Jain, Shrey, Gu, Yu, Lee, Ho Hin, Abacha, Asma Ben, Santamaria-Pang, Alberto, Guyman, Will, Sangani, Naiteek, Zhang, Sheng, Poon, Hoifung, Hyland, Stephanie, Bannur, Shruthi, Alvarez-Valle, Javier, Li, Xue, Garrett, John, McMillan, Alan, Rajguru, Gaurav, Maddi, Madhu, Vijayrania, Nilesh, Bhimai, Rehaan, Mecklenburg, Nick, Jain, Rupal, Holstein, Daniel, Gaur, Naveen, Aski, Vijay, Hwang, Jenq-Neng, Lin, Thomas, Tarapov, Ivan, Lungren, Matthew, and Wei, Mu

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

In this work, we present MedImageInsight, an open-source medical imaging embedding model. MedImageInsight is trained on medical images with associated text and labels across a diverse collection of domains, including X-Ray, CT, MRI, dermoscopy, OCT, fundus photography, ultrasound, histopathology, and mammography. Rigorous evaluations demonstrate MedImageInsight's ability to achieve state-of-the-art (SOTA) or human expert level performance across classification, image-image search, and fine-tuning tasks. Specifically, on public datasets, MedImageInsight achieves SOTA in CT 3D medical image retrieval, as well as SOTA in disease classification and search for chest X-ray, dermatology, and OCT imaging. Furthermore, MedImageInsight achieves human expert performance in bone age estimation (on both public and partner data), as well as AUC above 0.9 in most other domains. When paired with a text decoder, MedImageInsight achieves near SOTA level single image report findings generation with less than 10\% the parameters of other models. Compared to fine-tuning GPT-4o with only MIMIC-CXR data for the same task, MedImageInsight outperforms in clinical metrics, but underperforms on lexical metrics where GPT-4o sets a new SOTA. Importantly for regulatory purposes, MedImageInsight can generate ROC curves, adjust sensitivity and specificity based on clinical need, and provide evidence-based decision support through image-image search (which can also enable retrieval augmented generation). In an independent clinical evaluation of image-image search in chest X-ray, MedImageInsight outperformed every other publicly available foundation model evaluated by large margins (over 6 points AUC), and significantly outperformed other models in terms of AI fairness (across age and gender). We hope releasing MedImageInsight will help enhance collective progress in medical imaging AI research and development.

Published
2024

2. When do molecular polaritons behave like optical filters?

Author

Schwennicke, Kai, Koner, Arghadip, Pérez-Sánchez, Juan B., Xiong, Wei, Giebink, Noel C., Weichman, Marissa L., and Yuen-Zhou, Joel

Subjects
Physics - Chemical Physics, Physics - Optics, Quantum Physics
Abstract

This perspective outlines several linear optical effects featured by molecular polaritons arising in the collective strong light-matter coupling regime, focusing on the limit when the number of molecules per photon mode is large. We show that, under these circumstances, molecular absorption within a cavity can be understood as the overlap between the polariton transmission and bare molecular absorption spectra, suggesting that polaritons act in part as optical filters. This framework demystifies and provides a straightforward explanation for a large class of theoretical models of polaritonic phenomena, highlighting that similar effects might be achievable outside a cavity with shaped laser pulses. With a few modifications, this simple conceptual picture can also be adapted to understand the incoherent nonlinear response of polaritonic systems. However, we note that there are experimental observations in the collective regime that exhibit phenomena that go beyond this treatment. Our analysis underscores the importance of the notion that the field still needs to establish a clear distinction between polaritonic phenomena that can be fully explained through classical optics and those that require a more advanced theoretical framework. The linear optics approach presented here is exact when the number of molecules tends to infinity and is quite accurate for a large, but finite, number of molecules. We highlight the limitations of this treatment when the rates of the single-molecule processes that facilitate dark-state-to-polariton relaxation cannot be neglected and in systems under strong coupling with few molecules. Further exploration in these areas is needed to uncover novel polaritonic phenomena.

Published
2024

3. MAIRA-2: Grounded Radiology Report Generation

Author

Bannur, Shruthi, Bouzid, Kenza, Castro, Daniel C., Schwaighofer, Anton, Thieme, Anja, Bond-Taylor, Sam, Ilse, Maximilian, Pérez-García, Fernando, Salvatelli, Valentina, Sharma, Harshita, Meissen, Felix, Ranjit, Mercy, Srivastav, Shaury, Gong, Julia, Codella, Noel C. F., Falck, Fabian, Oktay, Ozan, Lungren, Matthew P., Wetscherek, Maria Teodora, Alvarez-Valle, Javier, and Hyland, Stephanie L.

Subjects
Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition
Abstract

Radiology reporting is a complex task requiring detailed medical image understanding and precise language generation, for which generative multimodal models offer a promising solution. However, to impact clinical practice, models must achieve a high level of both verifiable performance and utility. We augment the utility of automated report generation by incorporating localisation of individual findings on the image - a task we call grounded report generation - and enhance performance by incorporating realistic reporting context as inputs. We design a novel evaluation framework (RadFact) leveraging the logical inference capabilities of large language models (LLMs) to quantify report correctness and completeness at the level of individual sentences, while supporting the new task of grounded reporting. We develop MAIRA-2, a large radiology-specific multimodal model designed to generate chest X-ray reports with and without grounding. MAIRA-2 achieves state of the art on existing report generation benchmarks and establishes the novel task of grounded report generation., Comment: 72 pages, 21 figures. v2 updates the model and adds results on the PadChest-GR dataset

Published
2024

6. Multi-junction surface ion trap for quantum computing

Author

Sterk, J. D., Blain, M. G., Delaney, M., Haltli, R., Heller, E., Holterhoff, A. L., Jennings, T., Jimenez, N., Kozhanov, A., Meinelt, Z., Ou, E., Van Der Wall, J., Noel, C., and Stick, D.

Subjects
Quantum Physics, Physics - Atomic Physics
Abstract

Surface ion traps with two-dimensional layouts of trapping regions are natural architectures for storing large numbers of ions and supporting the connectivity needed to implement quantum algorithms. Many of the components and operations needed to fully exploit this architecture have already been demonstrated, including operation at cryogenic temperatures with low heating, low excitation transport, and ion control and detection with integrated photonics. Here we demonstrate a trap that addresses the scaling challenge of increasing power dissipation as the RF electrode increases in size. By raising the RF electrode and removing most of the insulating dielectric layer below it we reduce both ohmic and dielectric power dissipation. We also measure heating rates across a range of motional frequencies and for different voltage sources in a trap with a raised RF electrode but solid dielectric., Comment: 7 pages, 4 figures

Published
2024

7. Extracting accurate light-matter couplings from disordered polaritons

Author

Schwennicke, Kai, Giebink, Noel C., and Yuen-Zhou, Joel

Subjects
Physics - Chemical Physics, Physics - Optics, Quantum Physics
Abstract

The vacuum Rabi splitting (VRS) in molecular polaritons stands as a fundamental measure of collective light-matter coupling. Despite its significance, the impact of molecular disorder on VRS is not fully understood yet. This study delves into the complexities of VRS amidst various distributions and degrees of disorder. Our analysis provides precise analytical expressions for linear absorption, transmission, and reflection spectra, along with a "sum" rule, offering a straightforward protocol for extracting accurate collective light-matter coupling values from experimental data. Importantly, our study cautions against directly translating large VRS to the onset of ultrastrong coupling regime. Furthermore, for rectangular disorder, we witness the emergence of narrow side bands alongside a broad central peak, indicating an extended coherence lifetime even in the presence of substantial disorder. These findings not only enhance our understanding of VRS in disordered molecular systems but also open avenues for achieving prolonged coherence lifetimes between the cavity and molecules via the interplay of collective coupling and disorder.

Published
2024
Full Text
View/download PDF

9. 3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology

Author

Abacha, Asma Ben, Santamaria-Pang, Alberto, Lee, Ho Hin, Merkow, Jameson, Cai, Qin, Devarakonda, Surya Teja, Islam, Abdullah, Gong, Julia, Lungren, Matthew P., Lin, Thomas, Codella, Noel C, and Tarapov, Ivan

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

The increasing use of medical imaging in healthcare settings presents a significant challenge due to the increasing workload for radiologists, yet it also offers opportunity for enhancing healthcare outcomes if effectively leveraged. 3D image retrieval holds potential to reduce radiologist workloads by enabling clinicians to efficiently search through diagnostically similar or otherwise relevant cases, resulting in faster and more precise diagnoses. However, the field of 3D medical image retrieval is still emerging, lacking established evaluation benchmarks, comprehensive datasets, and thorough studies. This paper attempts to bridge this gap by introducing a novel benchmark for 3D Medical Image Retrieval (3D-MIR) that encompasses four different anatomies imaged with computed tomography. Using this benchmark, we explore a diverse set of search strategies that use aggregated 2D slices, 3D volumes, and multi-modal embeddings from popular multi-modal foundation models as queries. Quantitative and qualitative assessments of each approach are provided alongside an in-depth discussion that offers insight for future research. To promote the advancement of this field, our benchmark, dataset, and code are made publicly available.

Published
2023

10. Collective Polaritonic Effects on Chemical Dynamics Suppressed by Disorder

Author

Pérez-Sánchez, Juan B., Mellini, Federico, Giebink, Noel C., and Yuen-Zhou, Joel

Subjects
Quantum Physics, Condensed Matter - Disordered Systems and Neural Networks
Abstract

We present a powerful formalism, disordered collective dynamics using truncated equations (d-CUT-E), to simulate the ultrafast quantum dynamics of molecular polaritons in the collective strong coupling regime, where a disordered ensemble of $N\gg10^{6}$ molecules couples to a cavity mode. Notably, we can capture this dynamics with a cavity hosting a single \textit{effective} molecule with $\sim N_{bins}$ electronic states, where $N_{bins}\ll N$ is the number of bins discretizing the disorder distribution. Using d-CUT-E we conclude that strong coupling, as evaluated from linear optical spectra, can be a poor proxy for polariton chemistry. For highly disordered ensembles, total reaction yield upon broadband excitation is identical to that outside of the cavity, while narrowband excitation produces distinct reaction yields solely due to differences in the initial states prepared prior to the reaction., Comment: 16 pages, 12 figures

Published
2023
Full Text
View/download PDF

11. BCN20000: Dermoscopic Lesions in the Wild

Author

Hernández-Pérez, Carlos, Combalia, Marc, Podlipnik, Sebastian, Codella, Noel C. F., Rotemberg, Veronica, Halpern, Allan C., Reiter, Ofer, Carrera, Cristina, Barreiro, Alicia, Helba, Brian, Puig, Susana, Vilaplana, Veronica, and Malvehy, Josep

Published
2024
Full Text
View/download PDF

12. BCN20000: Dermoscopic Lesions in the Wild

Author

Carlos Hernández-Pérez, Marc Combalia, Sebastian Podlipnik, Noel C. F. Codella, Veronica Rotemberg, Allan C. Halpern, Ofer Reiter, Cristina Carrera, Alicia Barreiro, Brian Helba, Susana Puig, Veronica Vilaplana, and Josep Malvehy

Subjects
Science
Abstract

Abstract Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning from 2010 to 2016, collated at the Hospital Clínic in Barcelona, Spain. The BCN20000 dataset aims to address the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions in hard-to-diagnose locations such as those found in nails and mucosa, large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. Our dataset covers eight key diagnostic categories in dermoscopy, providing a diverse range of lesions for artificial intelligence model training. Furthermore, a ninth out-of-distribution (OOD) class is also present on the test set, comprised of lesions which could not be distinctively classified as any of the others. By providing a comprehensive collection of varied images, BCN20000 helps bridge the gap between the training data for machine learning models and the day-to-day practice of medical practitioners. Additionally, we present a set of baseline classifiers based on state-of-the-art neural networks, which can be extended by other researchers for further experimentation.

Published
2024
Full Text
View/download PDF

13. Colchicine for secondary prevention of ischaemic stroke and atherosclerotic events: a meta-analysis of randomised trialsResearch in context

Author

Aernoud T.L. Fiolet, Michiel H.F. Poorthuis, Tjerk S.J. Opstal, Pierre Amarenco, Kevin Emery Boczar, Ian Buysschaert, Charley Budgeon, Noel C. Chan, Jan H. Cornel, Sanjit S. Jolly, Jamie Layland, Robin Lemmens, Nathan Mewton, Stefan M. Nidorf, Domingo A. Pascual-Figal, Christopher Price, Binita Shah, Jean-Claude Tardif, Peter L. Thompson, Jan G.P. Tijssen, Georgios Tsivgoulis, Cathal Walsh, Yongjun Wang, Christian Weimar, John W. Eikelboom, Arend Mosterd, and Peter J. Kelly

Subjects
Colchicine, Meta-analysis, Stroke, MACE, Safety, Medicine (General), R5-920
Abstract

Summary: Background: Guidelines recommend low-dose colchicine for secondary prevention in cardiovascular disease, but uncertainty remains concerning its efficacy for stroke, efficacy in key subgroups and about uncommon but serious safety outcomes. Methods: In this trial-level meta-analysis, we searched bibliographic databases and trial registries form inception to May 16, 2024. We included randomised trials of colchicine for secondary prevention of ischaemic stroke and major adverse cardiovascular events (MACE: ischaemic stroke, myocardial infarction, coronary revascularisation, or cardiovascular death). Secondary outcomes were serious safety outcomes and mortality. A fixed-effect inverse-variance model was used to generate a pooled estimate of relative risk (RR) with 95% confidence intervals (CI). This study is registered with PROSPERO, CRD42024540320. Findings: Six trials involving 14,934 patients with prior stroke or coronary disease were included. In all patients, colchicine compared with placebo or no colchicine reduced the risk for ischaemic stroke by 27% (132 [1.8%] events versus 186 [2.5%] events, RR 0.73 [95% CI 0.58–0.90]) and MACE by 27% (505 [6.8%] events versus 693 [9.4%] events, with RR 0.73 [0.65–0.81]). Efficacy was consistent in key subgroups (females versus males, age below versus above 70, with versus without diabetes, statin versus non-statin users). Colchicine was not associated with an increase in serious safety outcomes: hospitalisation for pneumonia (109 [1.5%] versus 106 [1.5%], RR 0.99 [0.76–1.30]), cancer (247 [3.5%] versus 255 [3.6%], RR 0.97 [0.82–1.15]), and gastro-intestinal events (153 [2.1%] versus 135 [1.9%]), RR 1.15 [0.91–1.44]. There was no difference in all-cause death (201 [2.7%] versus 181 [2.4%], RR 1.09 [0.89–1.33]), cardiovascular death (70 [0.9%] versus 80 [1.1%], RR 0.89 [0.65–1.23]), or non-cardiovascular death (131 [1.8%] versus 101 [1.4%], RR 1.26 [0.98–1.64]). Interpretation: In patients with prior stroke or coronary disease, colchicine reduced ischaemic stroke and MACE, with consistent treatment effect in key subgroups, and did not increase serious safety events or death. Funding: There was no funding source for this study.

Published
2024
Full Text
View/download PDF

14. Food service management perspectives on reducing sodium content in foods served: Opportunities and challenges

Author

Reyes Mariana A., Robles Brenda, Wickramasekaran Ranjana N., Regos-Stewart Dalia, Barragan Noel C., and Kuo Tony

Subjects
sodium, diet, nutrition policy, public health, cardiovascular diseases, chronic disease prevention, Medicine
Abstract

Between Fall 2017 and Spring 2018, the Los Angeles County Sodium Reduction Initiative interviewed food service management leaders and staff from eight public and private institutions in Southern California (three universities, four hospitals, and one senior meal program) to identify opportunities and challenges in reducing sodium content for the foods they sell, serve, and produce. Interviews were transcribed, collated, and analyzed using content analysis with thematic sorting and coding. Interviewees identified several opportunities: (1) group purchasing through a large organizational membership; (2) a supportive organizational culture; (3) organized strategies to replace high-sodium products; and (4) access to software resources to manage food inventories. Challenges included (1) negative customer/staff receptivity to low-sodium options; (2) lack of kitchen infrastructure/equipment; (3) low availability of healthy foods; and (4) limited program evaluation capacity. Collectively, these findings provide practice-based insights into how these factors contributed to sodium reduction efforts in these institutions.

Published
2024
Full Text
View/download PDF

16. Colchicine for secondary prevention of ischaemic stroke and atherosclerotic events: a meta-analysis of randomised trials

Author

Fiolet, Aernoud T.L., Poorthuis, Michiel H.F., Opstal, Tjerk S.J., Amarenco, Pierre, Boczar, Kevin Emery, Buysschaert, Ian, Budgeon, Charley, Chan, Noel C., Cornel, Jan H., Jolly, Sanjit S., Layland, Jamie, Lemmens, Robin, Mewton, Nathan, Nidorf, Stefan M., Pascual-Figal, Domingo A., Price, Christopher, Shah, Binita, Tardif, Jean-Claude, Thompson, Peter L., Tijssen, Jan G.P., Tsivgoulis, Georgios, Walsh, Cathal, Wang, Yongjun, Weimar, Christian, Eikelboom, John W., Mosterd, Arend, and Kelly, Peter J.

Published
2024
Full Text
View/download PDF

17. Comorbidity of Type 2 Diabetes and Dementia among Hospitalized Patients in Los Angeles County: Hospitalization Outcomes and Costs, 2019–2021

Author

D’Artagnan M. Robinson, Dalia Regos-Stewart, Mariana A. Reyes, Tony Kuo, and Noel C. Barragan

Subjects
diabetes, Alzheimer’s disease, dementia, hospitalization, Diseases of the blood and blood-forming organs, RC633-647.5
Abstract

Hospitalizations for diabetes and dementia can impose a significant health and economic toll on older adults in the United States. This study sought to examine differences in hospitalization characteristics and outcomes associated with diabetes and dementia, separately and together, using 2019–2021 discharge record data from the California Department of Health Care Access and Information. The sampled group were residents of Los Angeles County who were aged 50+ at the time of the study. The multivariable linear regression analysis showed that compared to those with no diabetes or dementia, patients with diabetes alone exhibited the highest total charges, while those with comorbid diabetes and dementia exhibited lower charges (p < 0.05). The multinomial logistic regression found that patients with comorbid diabetes and dementia had the highest odds of having a length of stay of 7+ days (Adjusted Odds Ratio = 1.49; 95% Confidence Interval (CI) = 1.44–1.53). A matched case–control analysis revealed that comorbid diabetes and dementia were associated with significantly lower odds of hypertensive disease than diabetes alone (Matched Odds Ratio = 0.81; 95% CI = 0.67–0.97). Collectively, these results highlight the complex factors that may influence the variable hospitalization outcomes that are common occurrences in these three distinct disease profiles. Study findings suggest a need to consider these complexities when developing policies or strategies to improve hospitalization outcomes for these conditions.

Published
2023
Full Text
View/download PDF

18. Leveraging Community Pharmacies to Address Social Needs: A Promising Practice to Improve Healthcare Quality

Author

Tony Kuo, Noel C. Barragan, and Steven Chen

Subjects
community pharmacies, pharmacists, social needs, workforce development, healthcare quality, Pharmacy and materia medica, RS1-441
Abstract

Emerging research suggests that chronic conditions such as cardiovascular disease, diabetes, and asthma are often mediated by adverse social conditions that complicate their management. These conditions include circumstances such as lack of affordable housing, food insecurity, barriers to safe and reliable transportation, structural racism, and unequal access to healthcare or higher education. Although health systems cannot independently solve these problems, their infrastructure, funding resources, and well-trained workforce can be realigned to better address social needs created by them. For example, community pharmacies and the professionals they employ can be utilized and are well-positioned to deliver balanced, individualized clinical services, with a focus on the whole person. Because they have deep roots and presence in the community, especially in under-resourced neighborhoods, community pharmacies (independent and chain) represent local entities that community members recognize and trust. In this article, we provide case examples from California, United States, to illustrate and explore how community pharmacies can be leveraged to address patient social needs as part of their core responsibilities and overall strategy to improve healthcare quality.

Published
2024
Full Text
View/download PDF

19. Parenting Practices Are Associated With Out-of-School Physical Activity in US Adolescents in 2014.

Author

Hiya, Farhan, Lamour, Jean-Paul M., Khan, Anwar A., Wood, Robert, Rodriguez de la Vega, Pura E., Castro, Grettel, Ruiz, Juan G., and Barengo, Noel C.

Subjects
PHYSICAL activity, TEENAGERS, PARENT-child relationships, PARENTAL influences, ODDS ratio
Abstract

Introduction: Lack of physical activity (PA) is associated with obesity, diabetes, hypertension, cardiovascular diseases, and cancer. Parenting practices influence PA in young children. However, there is little evidence available for adolescents. We examined whether parenting practices were associated with out-of-school PA (OSPA) in US adolescents. Methods: This cross-sectional 2019 study analyzed data from the 2014 FLASHE study, a web-based, quota-sampled survey of parent–adolescent dyads. Inclusion required survey completion and parents to live with their teen (ages 12–17 y old). Physically limited adolescents were excluded. Dyads were stratified by teen age. Exposures included parental modeling, monitoring, facilitation, restriction, guided choice, and pressure. The outcomes of interest were OSPA Youth Activity Profile scores. Odds ratios (ORs) with 95% confidence intervals (CI) were calculated using adjusted logistic regressions. Results: A total of 1109 dyads were included. Guided choice increased odds of OSPA for 15- to 17-year-olds (OR = 2.12; 95% CI, 1.17–3.84). Facilitation increased odds of OSPA for 12- to 14-year-olds (OR = 2.21; 95% CI, 1.13–4.33). Monitoring decreased odds of OSPA for 15- to 17-year-olds (OR = 0.34; 95% CI, 0.20–0.57) and 12- to 14-year-olds (OR = 0.45; 95% CI, 0.27–0.74). Friend support increased odds of OSPA in 15- to 17-year-olds (OR = 4.03; 95% CI, 2.29–7.08) and 12- to 14-year-olds (OR = 3.05; 95% CI 1.69–5.51). Conclusion: Future interventions should prioritize (1) shared decision making for older teens, (2) access to PA opportunities for younger adolescents, and (3) promoting peer PA and friend support for everyone. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

25. Comparative RNA-seq analysis of resistant and susceptible banana genotypes reveals molecular mechanisms in response to banana bunchy top virus (BBTV) infection

Author

Darlon V. Lantican, Jen Daine L. Nocum, Anand Noel C. Manohar, Jay-Vee S. Mendoza, Roanne R. Gardoce, Grace C. Lachica, Lavernee S. Gueco, and Fe M. Dela Cueva

Subjects
Medicine, Science
Abstract

Abstract Bananas hold significant economic importance as an agricultural commodity, serving as a primary livelihood source, a favorite fruit, and a staple crop in various regions across the world. However, Banana bunchy top disease (BBTD), which is caused by banana bunchy top virus (BBTV), poses a considerable threat to banana cultivation. To understand the resistance mechanism and the interplay of host suitability factors in the presence of BBTV, we conducted RNA-seq-based comparative transcriptomics analysis on mock-inoculated and BBTV-inoculated samples from resistant (wild Musa balbisiana) and susceptible (Musa acuminata ‘Lakatan’) genotypes. We observed common patterns of expression for 62 differentially expressed genes (DEGs) in both genotypes, which represent the typical defense response of bananas to BBTV. Furthermore, we identified 99 DEGs exclusive to the 'Lakatan' banana cultivar, offering insights into the host factors and susceptibility mechanisms that facilitate successful BBTV infection. In parallel, we identified 151 DEGs unique to the wild M. balbisiana, shedding light on the multifaceted mechanisms of BBTV resistance, involving processes such as secondary metabolite biosynthesis, cell wall modification, and pathogen perception. Notably, our validation efforts via RT-qPCR confirmed the up-regulation of the glucuronoxylan 4-O-methyltransferase gene (14.28 fold-change increase), implicated in xylan modification and degradation. Furthermore, our experiments highlighted the potential recruitment of host's substrate adaptor ADO (30.31 fold-change increase) by BBTV, which may play a role in enhancing banana susceptibility to the viral pathogen. The DEGs identified in this work can be used as basis in designing associated gene markers for the precise integration of resistance genes in marker-assisted breeding programs. Furthermore, the findings can be applied to develop genome-edited banana cultivars targeting the resistance and susceptibility genes, thus developing novel cultivars that are resilient to important diseases.

Published
2023
Full Text
View/download PDF

31. Study of the exfoliation and functionalization of graphene from graphite flakes with plasma discharge in solution

Author

Liebgott, Q., Tousch, C. Da Silva, Letoffe, A., Ibrahim, D., Kabbara, H., Noel, C., Henrion, G., Herold, C., Royaud, I., Poncot, M., Fontana, S., and Cuynet, S.

Subjects
Physics - Applied Physics
Abstract

Graphene flakes were produced by nanosecond plasma discharge at atmospheric pressure between an electrode and the surface of distilled water, in which were placed graphite flakes. The discharge ionizes the gas and forms free radicals on the surface of the water, functionalizing the graphite flakes in solution. The plasma also gives enough energy to break the Van der Waals bonds between the graphene layers but not enough to break the covalent C-C bonds within the layers. Transmission electron microscopy confirmed the hexagonal structure of graphene sheets, and showed that they were monocrystalline. No contamination was found in the obtained nanomaterial. An unknown phenomenon has been found in the activated distilled water, making its electrical conductivity decrease with an increasing temperature. An acidification of the water is observed. The gas in which the discharge takes place plays a major role on the process, no exfoliation is observed if plasmogen argon gas is used., Comment: 13 pages, 22 figures

Published
2021

32. Pulsed discharge plasma for graphite exfoliation in liquid nitrogen

Author

Tousch, C. Da Silva, Liebgott, Q., Letoffe, A., Ibrahim, D., Kabbara, H., Noel, C., Henrion, G., Herold, C., Royaud, I., Poncot, M., Fontana, S., and Cuynet, S.

Subjects
Physics - Applied Physics, Physics - Plasma Physics
Abstract

Highly Oriented Pyrolytic Graphite was exfoliated via pulsed discharge plasma in liquid nitrogen. The potential mechanisms involved were investigated by observing the treated surface of the graphitic material and the obtained particles. Non-exfoliating defects from the plasma treatment were observed and experimental parameter were modified to counteract those. One experiment was performed without exposing the HOPG directly to the discharges so as to better understand the plasma role. The exfoliated particles were observed via TEM and SEM to evaluate the defects, the size, the purity and the crystallinity but no quantitative characterization of their thickness was possible so the actual number of layer of each particle is unknown. Nonetheless, few layers graphene (FLG) was successfully exfoliated through this process. The proposed mechanisms were extrapolated from the observation of the damaged HOPG surface and the obtained particles but the correlation found does not prove causation., Comment: 14 pages, 21 figures

Published
2021

38. A qualitative analysis of post-hoc interviews with multilevel participants of a randomized controlled trial of a community-based intervention.

Author

Nathan Kohrman, Mohamad Rashid, Roxana Flores, Ciantel Blyler, Noel C Barragan, Tony Kuo, Moira Inkelas, Steven Chen, Florian Rader, Susan Cheng, Christine Albert, Natalie A Bello, and Joseph Ebinger

Subjects
Medicine, Science
Abstract

IntroductionCommunity-based health interventions often demonstrate efficacy in clinical trial settings but fail to be implemented in the real-world. We sought to identify the key operational and contextual elements of the Los Angeles Barbershop Blood Pressure Study (LABBPS), an objectively successful community-based health intervention primed for real-world implementation. LABBPS was a cluster randomized control trial that paired the barbers of Black-owned barbershops with clinical pharmacists to manage uncontrolled hypertension in Black male patrons, demonstrating a substantial 21.6 mmHg reduction in systolic blood pressure. Despite this success, the LABBPS intervention has not expanded beyond the original clinical trial setting. The aim of this study was to determine the facilitating and limiting factors to expansion of the LABBPS intervention.MethodsWe undertook a qualitative assessment of semi-structured interviews with study participants performed after trial completion. Interviews included a total of 31 participants including 20 (6%) of the 319 LABBPS program participants ("patrons"), 10 (19%) barbers, and one (50%) clinical pharmacist. The semi-structured interviews were focused on perceptions of the medical system, study intervention, and influence of social factors on health.ResultsSeveral common themes emerged from thematic analysis of interview responses including: importance of care provided in a convenient and safe environment, individual responsibility for health and health-related behaviors, and engagement of trusted community members. In particular, patrons reported that receiving the intervention from their barber in a familiar environment positively influenced the formation of relationships with clinical pharmacists around shared efforts to improve medication adherence and healthy habits. All interviewee groups identified the trust diad, comprising the familiar environment and respected community member, as instrumental in increasing health-related behaviors to a degree not usually achieved by traditional healthcare providers.DiscussionIn conclusion, participants of an objectively successful community-based intervention trial consistently identified key features that could facilitate wider implementation and efficacy: social trust relationships, soliciting insights of trust bearers, and consistent engagement in a familiar community setting. These findings can help to inform the design and operations of future community-based studies and programs aiming to achieve a broad and sustainable impact.

Published
2024
Full Text
View/download PDF

39. Lasing in the Space Charge-Limited Current Regime

Author

Grede, Alex J. and Giebink, Noel C.

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

We introduce an analytical model for ideal organic laser diodes based on the argument that their intrinsic active layers necessitate operation in the bipolar space charge-limited current regime. Expressions for the threshold current and voltage agree well with drift-diffusion modeling of complete p-i-n devices and an analytical bound is established for laser operation in the presence of annihilation and excited-state absorption losses. These results establish a foundation for the development of organic laser diode technology.

Published
2020
Full Text
View/download PDF

40. Quantum Gates on Individually-Addressed Atomic Qubits Subject to Noisy Transverse Motion

Author

Cetina, M., Egan, L. N., Noel, C. A., Goldman, M. L., Risinger, A. R., Zhu, D., Biswas, D., and Monroe, C.

Subjects
Quantum Physics
Abstract

Individual trapped atomic qubits represent one of the most promising technologies to scale quantum computers, owing to their negligible idle errors and the ability to implement a full set of reconfigurable gate operations via focused optical fields. However, the fidelity of quantum gate operations can be limited by weak confinement of the atoms transverse to the laser. We present measurements of this effect by performing individually-addressed entangling gates in chains of up to 25 trapped atomic ions that are weakly confined along the chain axis. We present a model that accurately describes the observed decoherence from the residual heating of the ions caused by noisy electric fields. We propose to suppress these effects through the use of ancilla ions interspersed in the chain to sympathetically cool the qubit ions throughout a quantum circuit.

Published
2020

41. Enhanced optical nonlinearities under strong light-matter coupling

Author

Ribeiro, Raphael F., Campos-Gonzalez-Angulo, Jorge A., Giebink, Noel C., Xiong, Wei, and Yuen-Zhou, Joel

Subjects
Physics - Chemical Physics, Quantum Physics
Abstract

Optical microcavities and metallic nanostructures have been shown to significantly modulate the dynamics and spectroscopic response of molecular systems. We present a study of the nonlinear optics of a model consisting of $N$ anharmonic multilevel systems (e.g., Morse oscillators) undergoing collective strong coupling with a resonant infrared microcavity. We find that, under experimentally accessible conditions, molecular systems in microcavities may have nonlinear phenomena significantly intensified due to the high quality of polariton resonances and the enhanced microcavity electromagnetic energy density relative to free space. Particularly large enhancement of multiphoton absorption happens when multipolariton states are resonant with bare molecule multiphoton transitions. In particular, our model predicts two-photon absorption cross section enhancements by several orders of magnitude relative to free space when the Rabi splitting $\Omega_R$ is approximately equal to the molecular anharmonic shift $2\Delta$. Our results provide rough upper bounds to resonant nonlinear response enhancement factors as relaxation to dark states is treated phenomenologically. Notably, ensembles of two-level systems undergoing strong coupling with a cavity (described by the Tavis-Cummings model) show no such optical nonlinearity enhancements, highlighting the rich phenomenology afforded by multilevel anharmonic systems. Similar conclusions are expected to hold for excitonic systems that share features with our model (e.g., molecular dyes with accessible S_0 -> S_1 -> S_2 transitions) and strongly interact with a UV-visible cavity.

Published
2020
Full Text
View/download PDF

42. A Broader Study of Cross-Domain Few-Shot Learning

Author

Guo, Yunhui, Codella, Noel C., Karlinsky, Leonid, Codella, James V., Smith, John R., Saenko, Kate, Rosing, Tajana, and Feris, Rogerio

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Recent progress on few-shot learning largely relies on annotated data for meta-learning: base classes sampled from the same domain as the novel classes. However, in many applications, collecting data for meta-learning is infeasible or impossible. This leads to the cross-domain few-shot learning problem, where there is a large shift between base and novel class domains. While investigations of the cross-domain few-shot scenario exist, these works are limited to natural images that still contain a high degree of visual similarity. No work yet exists that examines few-shot learning across different imaging methods seen in real world scenarios, such as aerial and medical imaging. In this paper, we propose the Broader Study of Cross-Domain Few-Shot Learning (BSCD-FSL) benchmark, consisting of image data from a diverse assortment of image acquisition methods. This includes natural images, such as crop disease images, but additionally those that present with an increasing dissimilarity to natural images, such as satellite images, dermatology images, and radiology images. Extensive experiments on the proposed benchmark are performed to evaluate state-of-art meta-learning approaches, transfer learning approaches, and newer methods for cross-domain few-shot learning. The results demonstrate that state-of-art meta-learning methods are surprisingly outperformed by earlier meta-learning approaches, and all meta-learning methods underperform in relation to simple fine-tuning by 12.8% average accuracy. Performance gains previously observed with methods specialized for cross-domain few-shot learning vanish in this more challenging benchmark. Finally, accuracy of all methods tend to correlate with dataset similarity to natural images, verifying the value of the benchmark to better represent the diversity of data seen in practice and guiding future research., Comment: ECCV 2020. Website: https://www.learning-with-limited-labels.com/

Published
2019

44. Current Trends in Syphilis Mortality in the United States, 2015–2020

Author

Noel C. Barragan, Ranjana N. Wickramasekaran, Frank Sorvillo, Lisa V. Smith, and Tony Kuo

Subjects
syphilis, sexually transmitted infection, mortality, Specialties of internal medicine, RC581-951
Abstract

Rates of reported cases of syphilis have steadily increased since 2000 in the United States. However, despite the increase in cases, mortality from 2000–2014 declined. The following study examines the latest trends in syphilis-related deaths using 2015–2020 Multiple Cause of Death data. A total of 925 syphilis-related deaths were identified during the study period, 30% of which listed syphilis as the underlying cause of death. On average, age-adjusted syphilis mortality increased by 9.51% annually (95% CI = 5.41%–13.77%). Study findings indicate a marked increase in deaths attributed to syphilis, underscoring the need to more systematically and comprehensively address the growing sexually transmitted infection epidemic in the United States.

Published
2023
Full Text
View/download PDF

45. Comprehensive Medication Management as a Standard of Practice for Managing Uncontrolled Blood Pressure

Author

Kuo, Tony, Chen, Steven, Oh, Sang-Mi, Barragan, Noel C, and Committee, the American Heart Association Western States Chronic Disease Prevention and Management

Subjects
Biomedical and Clinical Sciences, Health Sciences, Patient Safety, Hypertension, 7.1 Individual care needs, blood pressure control, comprehensive medication management, medication adherence, team care, pharmacists, American Heart Association Western States Chronic Disease Prevention and Management Committee, Biomedical and clinical sciences, Health sciences
Published
2021

46. Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets

Author

Kinyanjui, Newton M., Odonga, Timothy, Cintas, Celia, Codella, Noel C. F., Panda, Rameswar, Sattigeri, Prasanna, and Varshney, Kush R.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Computers and Society, Statistics - Machine Learning
Abstract

Recent advances in computer vision and deep learning have led to breakthroughs in the development of automated skin image analysis. In particular, skin cancer classification models have achieved performance higher than trained expert dermatologists. However, no attempt has been made to evaluate the consistency in performance of machine learning models across populations with varying skin tones. In this paper, we present an approach to estimate skin tone in benchmark skin disease datasets, and investigate whether model performance is dependent on this measure. Specifically, we use individual typology angle (ITA) to approximate skin tone in dermatology datasets. We look at the distribution of ITA values to better understand skin color representation in two benchmark datasets: 1) the ISIC 2018 Challenge dataset, a collection of dermoscopic images of skin lesions for the detection of skin cancer, and 2) the SD-198 dataset, a collection of clinical images capturing a wide variety of skin diseases. To estimate ITA, we first develop segmentation models to isolate non-diseased areas of skin. We find that the majority of the data in the the two datasets have ITA values between 34.5{\deg} and 48{\deg}, which are associated with lighter skin, and is consistent with under-representation of darker skinned populations in these datasets. We also find no measurable correlation between performance of machine learning model and ITA values, though more comprehensive data is needed for further validation., Comment: NeurIPS 2019 Workshop on Fair ML for Health

Published
2019

47. BCN20000: Dermoscopic Lesions in the Wild

Author

Combalia, Marc, Codella, Noel C. F., Rotemberg, Veronica, Helba, Brian, Vilaplana, Veronica, Reiter, Ofer, Carrera, Cristina, Barreiro, Alicia, Halpern, Allan C., Puig, Susana, and Malvehy, Josep

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

This article summarizes the BCN20000 dataset, composed of 19424 dermoscopic images of skin lesions captured from 2010 to 2016 in the facilities of the Hospital Cl\'inic in Barcelona. With this dataset, we aim to study the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions found in hard-to-diagnose locations (nails and mucosa), large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. The BCN20000 will be provided to the participants of the ISIC Challenge 2019, where they will be asked to train algorithms to classify dermoscopic images of skin cancer automatically., Comment: Abstract for BCN20000

Published
2019

48. Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning

Author

Codella, Noel C. F., Hind, Michael, Ramamurthy, Karthikeyan Natesan, Campbell, Murray, Dhurandhar, Amit, Varshney, Kush R., Wei, Dennis, and Mojsilović, Aleksandra

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

Using machine learning in high-stakes applications often requires predictions to be accompanied by explanations comprehensible to the domain user, who has ultimate responsibility for decisions and outcomes. Recently, a new framework for providing explanations, called TED, has been proposed to provide meaningful explanations for predictions. This framework augments training data to include explanations elicited from domain users, in addition to features and labels. This approach ensures that explanations for predictions are tailored to the complexity expectations and domain knowledge of the consumer. In this paper, we build on this foundational work, by exploring more sophisticated instantiations of the TED framework and empirically evaluate their effectiveness in two diverse domains, chemical odor and skin cancer prediction. Results demonstrate that meaningful explanations can be reliably taught to machine learning algorithms, and in some cases, improving modeling accuracy., Comment: presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA. arXiv admin note: substantial text overlap with arXiv:1805.11648

Published
2019

49. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Author

Ong, Kanyin Liane, Stafford, Lauryn K, McLaughlin, Susan A, Boyko, Edward J, Vollset, Stein Emil, Smith, Amanda E, Dalton, Bronte E, Duprey, Joe, Cruz, Jessica A, Hagins, Hailey, Lindstedt, Paulina A, Aali, Amirali, Abate, Yohannes Habtegiorgis, Abate, Melsew Dagne, Abbasian, Mohammadreza, Abbasi-Kangevari, Zeinab, Abbasi-Kangevari, Mohsen, Abd ElHafeez, Samar, Abd-Rabu, Rami, Abdulah, Deldar Morad, Abdullah, Abu Yousuf Md, Abedi, Vida, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Abu-Gharbieh, Eman, Abu-Zaid, Ahmed, Adane, Tigist Demssew, Adane, Denberu Eshetie, Addo, Isaac Yeboah, Adegboye, Oyelola A, Adekanmbi, Victor, Adepoju, Abiola Victor, Adnani, Qorinah Estiningtyas Sakilah, Afolabi, Rotimi Felix, Agarwal, Gina, Aghdam, Zahra Babaei, Agudelo-Botero, Marcela, Aguilera Arriagada, Constanza Elizabeth, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahmad, Danish, Ahmad, Rizwan, Ahmad, Sajjad, Ahmad, Aqeel, Ahmadi, Ali, Ahmadi, Keivan, Ahmed, Ayman, Ahmed, Ali, Ahmed, Luai A, Ahmed, Syed Anees, Ajami, Marjan, Akinyemi, Rufus Olusola, Al Hamad, Hanadi, Al Hasan, Syed Mahfuz, AL-Ahdal, Tareq Mohammed Ali, Alalwan, Tariq A, Al-Aly, Ziyad, AlBataineh, Mohammad T, Alcalde-Rabanal, Jacqueline Elizabeth, Alemi, Sharifullah, Ali, Hassam, Alinia, Tahereh, Aljunid, Syed Mohamed, Almustanyir, Sami, Al-Raddadi, Rajaa M, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Amiri, Sohrab, Amusa, Ganiyu Adeniyi, Andrei, Catalina Liliana, Anjana, Ranjit Mohan, Ansar, Adnan, Ansari, Golnoosh, Ansari-Moghaddam, Alireza, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Aravkin, Aleksandr Y, Areda, Demelash, Arifin, Hidayat, Arkew, Mesay, Armocida, Benedetta, Ärnlöv, Johan, Artamonov, Anton A, Arulappan, Judie, Aruleba, Raphael Taiwo, Arumugam, Ashokan, Aryan, Zahra, Asemu, Mulu Tiruneh, Asghari-Jafarabadi, Mohammad, Askari, Elaheh, Asmelash, Daniel, Astell-Burt, Thomas, Athar, Mohammad, Athari, Seyyed Shamsadin, Atout, Maha Moh'd Wahbi, Avila-Burgos, Leticia, Awaisu, Ahmed, Azadnajafabad, Sina, B, Darshan B, Babamohamadi, Hassan, Badar, Muhammad, Badawi, Alaa, Badiye, Ashish D, Baghcheghi, Nayereh, Bagheri, Nasser, Bagherieh, Sara, Bah, Sulaiman, Bahadory, Saeed, Bai, Ruhai, Baig, Atif Amin, Baltatu, Ovidiu Constantin, Baradaran, Hamid Reza, Barchitta, Martina, Bardhan, Mainak, Barengo, Noel C, Bärnighausen, Till Winfried, Barone, Mark Thomaz Ugliara, Barone-Adesi, Francesco, Barrow, Amadou, Bashiri, Hamideh, Basiru, Afisu, Basu, Sanjay, Basu, Saurav, Batiha, Abdul-Monim Mohammad, Batra, Kavita, Bayih, Mulat Tirfie, Bayileyegn, Nebiyou Simegnew, Behnoush, Amir Hossein, Bekele, Alehegn Bekele, Belete, Melaku Ashagrie, Belgaumi, Uzma Iqbal, Belo, Luis, Bennett, Derrick A, Bensenor, Isabela M, Berhe, Kidanemaryam, Berhie, Alemshet Yirga, Bhaskar, Sonu, Bhat, Ajay Nagesh, Bhatti, Jasvinder Singh, Bikbov, Boris, Bilal, Faiq, Bintoro, Bagas Suryo, Bitaraf, Saeid, Bitra, Veera R, Bjegovic-Mikanovic, Vesna, Bodolica, Virginia, Boloor, Archith, Brauer, Michael, Brazo-Sayavera, Javier, Brenner, Hermann, Butt, Zahid A, Calina, Daniela, Campos, Luciana Aparecida, Campos-Nonato, Ismael R, Cao, Yin, Cao, Chao, Car, Josip, Carvalho, Márcia, Castañeda-Orjuela, Carlos A, Catalá-López, Ferrán, Cerin, Ester, Chadwick, Joshua, Chandrasekar, Eeshwar K, Chanie, Gashaw Sisay, Charan, Jaykaran, Chattu, Vijay Kumar, Chauhan, Kirti, Cheema, Huzaifa Ahmad, Chekol Abebe, Endeshaw, Chen, Simiao, Cherbuin, Nicolas, Chichagi, Fatemeh, Chidambaram, Saravana Babu, Cho, William C S, Choudhari, Sonali Gajanan, Chowdhury, Rajiv, Chowdhury, Enayet Karim, Chu, Dinh-Toi, Chukwu, Isaac Sunday, Chung, Sheng-Chia, Coberly, Kaleb, Columbus, Alyssa, Contreras, Daniela, Cousin, Ewerton, Criqui, Michael H, Cruz-Martins, Natália, Cuschieri, Sarah, Dabo, Bashir, Dadras, Omid, Dai, Xiaochen, Damasceno, Albertino Antonio Moura, Dandona, Rakhi, Dandona, Lalit, Das, Saswati, Dascalu, Ana Maria, Dash, Nihar Ranjan, Dashti, Mohsen, Dávila-Cervantes, Claudio Alberto, De la Cruz-Góngora, Vanessa, Debele, Gebiso Roba, Delpasand, Kourosh, Demisse, Fitsum Wolde, Demissie, Getu Debalkie, Deng, Xinlei, Denova-Gutiérrez, Edgar, Deo, Salil V, Dervišević, Emina, Desai, Hardik Dineshbhai, Desale, Aragaw Tesfaw, Dessie, Anteneh Mengist, Desta, Fikreab, Dewan, Syed Masudur Rahman, Dey, Sourav, Dhama, Kuldeep, Dhimal, Meghnath, Diao, Nancy, Diaz, Daniel, Dinu, Monica, Diress, Mengistie, Djalalinia, Shirin, Doan, Linh Phuong, Dongarwar, Deepa, dos Santos Figueiredo, Francisco Winter, Duncan, Bruce B, Dutta, Siddhartha, Dziedzic, Arkadiusz Marian, Edinur, Hisham Atan, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Elgendy, Islam Y, Elhadi, Muhammed, El-Huneidi, Waseem, Elmeligy, Omar Abdelsadek Abdou, Elmonem, Mohamed A, Endeshaw, Destaw, Esayas, Hawi Leul, Eshetu, Habitu Birhan, Etaee, Farshid, Fadhil, Ibtihal, Fagbamigbe, Adeniyi Francis, Fahim, Ayesha, Falahi, Shahab, Faris, MoezAlIslam Ezzat Mahmoud, Farrokhpour, Hossein, Farzadfar, Farshad, Fatehizadeh, Ali, Fazli, Ghazal, Feng, Xiaoqi, Ferede, Tomas Y, Fischer, Florian, Flood, David, Forouhari, Ali, Foroumadi, Roham, Foroutan Koudehi, Masoumeh, Gaidhane, Abhay Motiramji, Gaihre, Santosh, Gaipov, Abduzhappar, Galali, Yaseen, Ganesan, Balasankar, Garcia-Gordillo, MA, Gautam, Rupesh K, Gebrehiwot, Mesfin, Gebrekidan, Kahsu Gebrekirstos, Gebremeskel, Teferi Gebru, Getacher, Lemma, Ghadirian, Fataneh, Ghamari, Seyyed-Hadi, Ghasemi Nour, Mohammad, Ghassemi, Fariba, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Gopalani, Sameer Vali, Guadie, Habtamu Alganeh, Guan, Shi-Yang, Gudayu, Temesgen Worku, Guimarães, Rafael Alves, Guled, Rashid Abdi, Gupta, Rajeev, Gupta, Kartik, Gupta, Veer Bala, Gupta, Vivek Kumar, Gyawali, Bishal, Haddadi, Rasool, Hadi, Najah R, Haile, Teklehaimanot Gereziher, Hajibeygi, Ramtin, Haj-Mirzaian, Arvin, Halwani, Rabih, Hamidi, Samer, Hankey, Graeme J, Hannan, Md Abdul, Haque, Shafiul, Harandi, Hamid, Harlianto, Netanja I, Hasan, S M Mahmudul, Hasan, Syed Shahzad, Hasani, Hamidreza, Hassanipour, Soheil, Hassen, Mohammed Bheser, Haubold, Johannes, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Hessami, Kamran, Hiraike, Yuta, Holla, Ramesh, Hossain, Sahadat, Hossain, Md Shakhaoat, Hosseini, Mohammad-Salar, Hosseinzadeh, Mehdi, Hosseinzadeh, Hassan, Huang, Junjie, Huda, Md Nazmul, Hussain, Salman, Huynh, Hong-Han, Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Ikeda, Nayu, Ilic, Irena M, Ilic, Milena D, Inbaraj, Leeberk Raja, Iqbal, Afrin, Islam, Sheikh Mohammed Shariful, Islam, Rakibul M, Ismail, Nahlah Elkudssiah, Iso, Hiroyasu, Isola, Gaetano, Itumalla, Ramaiah, Iwagami, Masao, Iwu, Chidozie C D, Iyamu, Ihoghosa Osamuyi, Iyasu, Assefa N, Jacob, Louis, Jafarzadeh, Abdollah, Jahrami, Haitham, Jain, Rajesh, Jaja, Chinwe, Jamalpoor, Zahra, Jamshidi, Elham, Janakiraman, Balamurugan, Jayanna, Krishnamurthy, Jayapal, Sathish Kumar, Jayaram, Shubha, Jayawardena, Ranil, Jebai, Rime, Jeong, Wonjeong, Jin, Yinzi, Jokar, Mohammad, Jonas, Jost B, Joseph, Nitin, Joseph, Abel, Joshua, Charity Ehimwenma, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Kaambwa, Billingsley, Kabir, Ali, Kabthymer, Robel Hussen, Kadashetti, Vidya, Kahe, Farima, Kalhor, Rohollah, Kandel, Himal, Karanth, Shama D, Karaye, Ibraheem M, Karkhah, Samad, Katoto, Patrick DMC, Kaur, Navjot, Kazemian, Sina, Kebede, Sewnet Adem, Khader, Yousef Saleh, Khajuria, Himanshu, Khalaji, Amirmohammad, Khan, Moien AB, Khan, Maseer, Khan, Ajmal, Khanal, Saval, Khatatbeh, Moawiah Mohammad, Khater, Amir M, Khateri, Sorour, khorashadizadeh, Fatemeh, Khubchandani, Jagdish, Kibret, Biruk Getahun, Kim, Min Seo, Kimokoti, Ruth W, Kisa, Adnan, Kivimäki, Mika, Kolahi, Ali-Asghar, Komaki, Somayeh, Kompani, Farzad, Koohestani, Hamid Reza, Korzh, Oleksii, Kostev, Karel, Kothari, Nikhil, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Yuvaraj, Kuate Defo, Barthelemy, Kuddus, Mohammed, Kuddus, Md Abdul, Kumar, Rakesh, Kumar, Harish, Kundu, Satyajit, Kurniasari, Maria Dyah, Kuttikkattu, Ambily, La Vecchia, Carlo, Lallukka, Tea, Larijani, Bagher, Larsson, Anders O, Latief, Kamaluddin, Lawal, Basira Kankia, Le, Thao Thi Thu, Le, Trang Thi Bich, Lee, Shaun Wen Huey, Lee, Munjae, Lee, Wei-Chen, Lee, Paul H, Lee, Sang-woong, Lee, Seung Won, Legesse, Samson Mideksa, Lenzi, Jacopo, Li, Yongze, Li, Ming-Chieh, Lim, Stephen S, Lim, Lee-Ling, Liu, Xuefeng, Liu, Chaojie, Lo, Chun-Han, Lopes, Graciliana, Lorkowski, Stefan, Lozano, Rafael, Lucchetti, Giancarlo, Maghazachi, Azzam A, Mahasha, Phetole Walter, Mahjoub, Soleiman, Mahmoud, Mansour Adam, Mahmoudi, Razzagh, Mahmoudimanesh, Marzieh, Mai, Anh Tuan, Majeed, Azeem, Majma Sanaye, Pantea, Makris, Konstantinos Christos, Malhotra, Kashish, Malik, Ahmad Azam, Malik, Iram, Mallhi, Tauqeer Hussain, Malta, Deborah Carvalho, Mamun, Abdullah A, Mansouri, Borhan, Marateb, Hamid Reza, Mardi, Parham, Martini, Santi, Martorell, Miquel, Marzo, Roy Rillera, Masoudi, Reza, Masoudi, Sahar, Mathews, Elezebeth, Maugeri, Andrea, Mazzaglia, Giampiero, Mekonnen, Teferi, Meshkat, Mahboobeh, Mestrovic, Tomislav, Miao Jonasson, Junmei, Miazgowski, Tomasz, Michalek, Irmina Maria, Minh, Le Huu Nhat, Mini, GK, Miranda, J Jaime, Mirfakhraie, Reza, Mirrakhimov, Erkin M, Mirza-Aghazadeh-Attari, Mohammad, Misganaw, Awoke, Misgina, Kebede Haile, Mishra, Manish, Moazen, Babak, Mohamed, Nouh Saad, Mohammadi, Esmaeil, Mohammadi, Mohsen, Mohammadian-Hafshejani, Abdollah, Mohammadshahi, Marita, Mohseni, Alireza, Mojiri-forushani, Hoda, Mokdad, Ali H, Momtazmanesh, Sara, Monasta, Lorenzo, Moniruzzaman, Md, Mons, Ute, Montazeri, Fateme, Moodi Ghalibaf, AmirAli, Moradi, Yousef, Moradi, Maryam, Moradi Sarabi, Mostafa, Morovatdar, Negar, Morrison, Shane Douglas, Morze, Jakub, Mossialos, Elias, Mostafavi, Ebrahim, Mueller, Ulrich Otto, Mulita, Francesk, Mulita, Admir, Murillo-Zamora, Efrén, Musa, Kamarul Imran, Mwita, Julius C, Nagaraju, Shankar Prasad, Naghavi, Mohsen, Nainu, Firzan, Nair, Tapas Sadasivan, Najmuldeen, Hastyar Hama Rashid, Nangia, Vinay, Nargus, Shumaila, Naser, Abdallah Y, Nassereldine, Hasan, Natto, Zuhair S, Nauman, Javaid, Nayak, Biswa Prakash, Ndejjo, Rawlance, Negash, Hadush, Negoi, Ruxandra Irina, Nguyen, Hau Thi Hien, Nguyen, Dang H, Nguyen, Phat Tuan, Nguyen, Van Thanh, Nguyen, Hien Quang, Niazi, Robina Khan, Nigatu, Yeshambel T, Ningrum, Dina Nur Anggraini, Nizam, Muhammad A, Nnyanzi, Lawrence Achilles, Noreen, Mamoona, Noubiap, Jean Jacques, Nzoputam, Ogochukwu Janet, Nzoputam, Chimezie Igwegbe, Oancea, Bogdan, Odogwu, Nkechi Martina, Odukoya, Oluwakemi Ololade, Ojha, Vivek Anand, Okati-Aliabad, Hassan, Okekunle, Akinkunmi Paul, Okonji, Osaretin Christabel, Okwute, Patrick Godwin, Olufadewa, Isaac Iyinoluwa, Onwujekwe, Obinna E, Ordak, Michal, Ortiz, Alberto, Osuagwu, Uchechukwu Levi, Oulhaj, Abderrahim, Owolabi, Mayowa O, Padron-Monedero, Alicia, Padubidri, Jagadish Rao, Palladino, Raffaele, Panagiotakos, Demosthenes, Panda-Jonas, Songhomitra, Pandey, Ashok, Pandey, Anamika, Pandi-Perumal, Seithikurippu R, Pantea Stoian, Anca Mihaela, Pardhan, Shahina, Parekh, Tarang, Parekh, Utsav, Pasovic, Maja, Patel, Jay, Patel, Jenil R, Paudel, Uttam, Pepito, Veincent Christian Filipino, Pereira, Marcos, Perico, Norberto, Perna, Simone, Petcu, Ionela-Roxana, Petermann-Rocha, Fanny Emily, Podder, Vivek, Postma, Maarten J, Pourali, Ghazaleh, Pourtaheri, Naeimeh, Prates, Elton Junio Sady, Qadir, Mirza Muhammad Fahd, Qattea, Ibrahim, Raee, Pourya, Rafique, Ibrar, Rahimi, Mehran, Rahimifard, Mahban, Rahimi-Movaghar, Vafa, Rahman, Md Obaidur, Rahman, Muhammad Aziz, Rahman, Mohammad Hifz Ur, Rahman, Mosiur, Rahman, Md Mosfequr, Rahmani, Mohamed, Rahmani, Shayan, Rahmanian, Vahid, Rahmawaty, Setyaningrum, Rahnavard, Niloufar, Rajbhandari, Bibek, Ram, Pradhum, Ramazanu, Sheena, Rana, Juwel, Rancic, Nemanja, Ranjha, Muhammad Modassar Ali Nawaz, Rao, Chythra R, Rapaka, Deepthi, Rasali, Drona Prakash, Rashedi, Sina, Rashedi, Vahid, Rashid, Ahmed Mustafa, Rashidi, Mohammad-Mahdi, Ratan, Zubair Ahmed, Rawaf, Salman, Rawal, Lal, Redwan, Elrashdy Moustafa Mohamed, Remuzzi, Giuseppe, Rengasamy, Kannan RR, Renzaho, Andre M N, Reyes, Luis Felipe, Rezaei, Nima, Rezaei, Nazila, Rezaeian, Mohsen, Rezazadeh, Hossein, Riahi, Seyed Mohammad, Rias, Yohanes Andy, Riaz, Muhammad, Ribeiro, Daniela, Rodrigues, Mónica, Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Rohloff, Peter, Roshandel, Gholamreza, Roustazadeh, Abazar, Rwegerera, Godfrey M, Saad, Aly M A, Saber-Ayad, Maha Mohamed, Sabour, Siamak, Sabzmakan, Leila, Saddik, Basema, Sadeghi, Erfan, Saeed, Umar, Saeedi Moghaddam, Sahar, Safi, Sare, Safi, Sher Zaman, Saghazadeh, Amene, Saheb Sharif-Askari, Narjes, Saheb Sharif-Askari, Fatemeh, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahoo, Harihar, Saif-Ur-Rahman, KM, Sajid, Mirza Rizwan, Salahi, Sarvenaz, Salahi, Saina, Saleh, Mohamed A, Salehi, Mohammad Amin, Salomon, Joshua A, Sanabria, Juan, Sanjeev, Rama Krishna, Sanmarchi, Francesco, Santric-Milicevic, Milena M, Sarasmita, Made Ary, Sargazi, Saman, Sathian, Brijesh, Sathish, Thirunavukkarasu, Sawhney, Monika, Schlaich, Markus P, Schmidt, Maria Inês, Schuermans, Art, Seidu, Abdul-Aziz, Senthil Kumar, Nachimuthu, Sepanlou, Sadaf G, Sethi, Yashendra, Seylani, Allen, Shabany, Maryam, Shafaghat, Tahereh, Shafeghat, Melika, Shafie, Mahan, Shah, Nilay S, Shahid, Samiah, Shaikh, Masood Ali, Shanawaz, Mohd, Shannawaz, Mohammed, Sharfaei, Sadaf, Shashamo, Bereket Beyene, Shiri, Rahman, Shittu, Aminu, Shivakumar, K M, Shivalli, Siddharudha, Shobeiri, Parnian, Shokri, Fereshteh, Shuval, Kerem, Sibhat, Migbar Mekonnen, Silva, Luís Manuel Lopes Rodrigues, Simpson, Colin R, Singh, Jasvinder A, Singh, Paramdeep, Singh, Surjit, Siraj, Md Shahjahan, Skryabina, Anna Aleksandrovna, Sohag, Abdullah Al Mamun, Soleimani, Hamidreza, Solikhah, Solikhah, Soltani-Zangbar, Mohammad Sadegh, Somayaji, Ranjani, Sorensen, Reed J D, Starodubova, Antonina V, Sujata, Sujata, Suleman, Muhammad, Sun, Jing, Sundström, Johan, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabatabaeizadeh, Seyed-Amir, Tabish, Mohammad, Taheri, Majid, Taheri, Ensiyeh, Taki, Elahe, Tamuzi, Jacques JL Lukenze, Tan, Ker-Kan, Tat, Nathan Y, Taye, Birhan Tsegaw, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Tesler, Riki, Thangaraju, Pugazhenthan, Thankappan, Kavumpurathu Raman, Thapa, Rajshree, Tharwat, Samar, Thomas, Nihal, Ticoalu, Jansje Henny Vera, Tiyuri, Amir, Tonelli, Marcello, Tovani-Palone, Marcos Roberto, Trico, Domenico, Trihandini, Indang, Tripathy, Jaya Prasad, Tromans, Samuel Joseph, Tsegay, Guesh Mebrahtom, Tualeka, Abdul Rohim, Tufa, Derara Girma, Tyrovolas, Stefanos, Ullah, Sana, Upadhyay, Era, Vahabi, Seyed Mohammad, Vaithinathan, Asokan Govindaraj, Valizadeh, Rohollah, van Daalen, Kim Robin, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vaziri, Siavash, Verma, Madhur verma, Verras, Georgios-Ioannis, Vo, Danh Cao, Wagaye, Birhanu, Waheed, Yasir, Wang, Ziyue, Wang, Yanqing, Wang, Cong, Wang, Fang, Wassie, Gizachew Tadesse, Wei, Melissa Y Wei, Weldemariam, Abrha Hailay, Westerman, Ronny, Wickramasinghe, Nuwan Darshana, Wu, YiFan, Wulandari, Ratna DWI, Xia, Juan, Xiao, Hong, Xu, Suowen, Xu, Xiaoyue, Yada, Dereje Y, Yang, Lin, Yatsuya, Hiroshi, Yesiltepe, Metin, Yi, Siyan, Yohannis, Hunachew Kibret, Yonemoto, Naohiro, You, Yuyi, Zaman, Sojib Bin, Zamora, Nelson, Zare, Iman, Zarea, Kourosh, Zarrintan, Armin, Zastrozhin, Mikhail Sergeevich, Zeru, Naod Gebrekrstos, Zhang, Zhi-Jiang, Zhong, Chenwen, Zhou, Jingjing, Zielińska, Magdalena, Zikarg, Yossef Teshome, Zodpey, Sanjay, Zoladl, Mohammad, Zou, Zhiyong, Zumla, Alimuddin, Zuniga, Yves Miel H, Magliano, Dianna J, Murray, Christopher J L, Hay, Simon I, and Vos, Theo

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results