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1. Alignment of Doctors’ Understanding of Treatment Burden Priorities and Chronic Heart Failure Patients’ Experiences: A Nominal Group Technique Consultation

Author

Cardona M, Sav A, Michaleff ZA, Thomas ST, and Dobler CC

Subjects
patient priorities, barriers, qualitative studies, older adults, Medicine (General), R5-920
Abstract

Magnolia Cardona,1,2 Adem Sav,3 Zoe A Michaleff,1 Sarah T Thomas,2 Claudia C Dobler1,4 1Institute for Evidence Based Healthcare, Bond University, Robina, Queensland, Australia; 2Gold Coast Hospital and Health Service, Southport, Queensland, Australia; 3School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia; 4The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, AustraliaCorrespondence: Magnolia Cardona, Institute for Evidence-Based Healthcare, Faculty of Health Sciences and Medicine Level 4, HSM Building 5, Bond University, Robina, Queensland, 4226, Australia, Tel +61 7 5595 0170, Email mcardona@bond.edu.auPurpose: To identify and rank areas of treatment burden in chronic heart failure (CHF), including solutions, that should be discussed during the clinical encounter from a patient, and doctors’ perspective.Patients and Methods: Patients with CHF and clinicians managing heart failure were invited. Nominal group technique sessions held either face to face or online in 2021– 2022, with individual identification of priorities and voting on ranking.Results: Four patient groups (N=22) and one doctor group (N=5) were held. For patients with heart failure, in descending order of priority Doctor-patient communication, Inefficiencies of the healthcare system, Healthcare access issues, Cost implications of treatment, Psychosocial impacts on patients and their families, and Impact of treatment work were the most important treatment burdens. Priorities independently identified by the doctors aligned with the patients’ but ranking differed. Patient solutions ranged from involvement of nurses or pharmacists to enhance understanding of discharge planning, through to linkage between health information systems, and maintaining strong family or social support networks. Doctors’ solutions covered timing medicines with activities of daily living, patient education on the importance of compliance, medication reviews to overcome clinical inertia, and routine clinical audits.Conclusion: The top treatment burden priorities for CHF patients were related to interaction with clinicians and health system inefficiencies, whereas doctors were generally aware of patients’ treatment burden but tended to focus on the complexity of the direct treatment work. Addressing the priority issues identified here can commence with clinicians becoming aware of the issues that matter to patients and proactively discussing feasible immediate and longer-term solutions during clinical encounters.Keywords: patient priorities, barriers, qualitative studies, older adults

Published
2023

2. Treatment Burden Discussion in Clinical Encounters: Priorities of COPD Patients, Carers and Physicians

Author

Sav A, Thomas ST, Cardona M, Michaleff ZA, and Dobler CC

Subjects
copd, burden of treatment, treatment burden, nominal group technique, Diseases of the respiratory system, RC705-779
Abstract

Adem Sav,1 Sarah T Thomas,2 Magnolia Cardona,3,4 Zoe A Michaleff,4,5 Claudia C Dobler3,4,6 1School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia; 2Gold Coast University Hospital, Southport, Queensland, Australia; 3Evidence-Based Practice Professorial Unit, Gold Coast Hospital, Southport, Queensland, Australia; 4Institute for Evidence Based Healthcare, Bond University, Gold Coast, Queensland, Australia; 5Northern NSW Local Health District, Lismore, New South Wales, Australia; 6The George Institute for Global Health, University of New South Wales, Kensington, New South Wales, AustraliaCorrespondence: Adem Sav, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia, Tel +61 7 3138 5795, Email adem.sav@qut.edu.auPurpose: Many people with chronic obstructive pulmonary disease (COPD) feel overburdened with the treatment and management of their illness. Although research has begun to shed light on how COPD patients experience treatment burden, most of what we know is limited to personal experiences of patients. The aim of this study is to identify and prioritise areas of treatment burden that should be discussed during the clinical encounter from the perspectives of COPD patients, carers, and respiratory physicians.Patients and Methods: Data were collected from participants using the nominal group technique. Five nominal group sessions were conducted in total (n = 31); three sessions with patients (n = 18), one with carers (n = 7) and another with respiratory physicians (pulmonologists or chest physicians) (n = 6). Each session was recorded and analyzed using thematic analysis.Results: Going beyond understanding patients’ and carers’ experiences of treatment burden, this study offers a practical viewpoint of what should be discussed in a clinical encounter. Each group of participants contextualized treatment burden issues for discussion from their own perspectives. There was strong agreement, however, across the groups that difficulties accessing healthcare, lack of education and information, and worry about COPD treatment and prognosis were the most important treatment burden priorities for discussion.Conclusion: Understanding and creating opportunities to discuss these issues in a clinical encounter is important in not only reducing treatment burden but also improving health outcomes and quality of life for COPD patients and their carers.Keywords: COPD, burden of treatment, treatment burden, nominal group technique

Published
2022

3. Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data

Author

Akkus, Atilla, Li, Mingjie, Chu, Junjie, Backes, Michael, Zhang, Yang, and Sav, Sinem

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

Large language models (LLMs) have shown considerable success in a range of domain-specific tasks, especially after fine-tuning. However, fine-tuning with real-world data usually leads to privacy risks, particularly when the fine-tuning samples exist in the pre-training data. To avoid the shortcomings of real data, developers often employ methods to automatically generate synthetic data for fine-tuning, as data generated by traditional models are often far away from the real-world pertaining data. However, given the advanced capabilities of LLMs, the distinction between real data and LLM-generated data has become negligible, which may also lead to privacy risks like real data. In this paper, we present an empirical analysis of this underexplored issue by investigating a key question: "Does fine-tuning with LLM-generated data enhance privacy, or does it pose additional privacy risks?" Based on the structure of LLM's generated data, our research focuses on two primary approaches to fine-tuning with generated data: supervised fine-tuning with unstructured generated data and self-instruct tuning. The number of successful Personal Information Identifier (PII) extractions for Pythia after fine-tuning our generated data raised over $20\%$. Furthermore, the ROC-AUC score of membership inference attacks for Pythia-6.9b after self-instruct methods also achieves more than $40\%$ improvements on ROC-AUC score than base models. The results indicate the potential privacy risks in LLMs when fine-tuning with the generated data.

Published
2024

4. CURE: Privacy-Preserving Split Learning Done Right

Author

Kanpak, Halil Ibrahim, Shabbir, Aqsa, Genç, Esra, Küpçü, Alptekin, and Sav, Sinem

Subjects
Computer Science - Cryptography and Security
Abstract

Training deep neural networks often requires large-scale datasets, necessitating storage and processing on cloud servers due to computational constraints. The procedures must follow strict privacy regulations in domains like healthcare. Split Learning (SL), a framework that divides model layers between client(s) and server(s), is widely adopted for distributed model training. While Split Learning reduces privacy risks by limiting server access to the full parameter set, previous research has identified that intermediate outputs exchanged between server and client can compromise client's data privacy. Homomorphic encryption (HE)-based solutions exist for this scenario but often impose prohibitive computational burdens. To address these challenges, we propose CURE, a novel system based on HE, that encrypts only the server side of the model and optionally the data. CURE enables secure SL while substantially improving communication and parallelization through advanced packing techniques. We propose two packing schemes that consume one HE level for one-layer networks and generalize our solutions to n-layer neural networks. We demonstrate that CURE can achieve similar accuracy to plaintext SL while being 16x more efficient in terms of the runtime compared to the state-of-the-art privacy-preserving alternatives.

Published
2024

5. How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study

Author

Mitic, Natalija, Pyrgelis, Apostolos, and Sav, Sinem

Subjects
Computer Science - Cryptography and Security
Abstract

In this paper, we address the problem of privacy-preserving hyperparameter (HP) tuning for cross-silo federated learning (FL). We first perform a comprehensive measurement study that benchmarks various HP strategies suitable for FL. Our benchmarks show that the optimal parameters of the FL server, e.g., the learning rate, can be accurately and efficiently tuned based on the HPs found by each client on its local data. We demonstrate that HP averaging is suitable for iid settings, while density-based clustering can uncover the optimal set of parameters in non-iid ones. Then, to prevent information leakage from the exchange of the clients' local HPs, we design and implement PrivTuna, a novel framework for privacy-preserving HP tuning using multiparty homomorphic encryption. We use PrivTuna to implement privacy-preserving federated averaging and density-based clustering, and we experimentally evaluate its performance demonstrating its computation/communication efficiency and its precision in tuning hyperparameters.

Published
2024

6. slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference

Author

Intoci, Francesco, Sav, Sinem, Pyrgelis, Apostolos, Bossuat, Jean-Philippe, Troncoso-Pastoriza, Juan Ramon, and Hubaux, Jean-Pierre

Subjects
Computer Science - Cryptography and Security
Abstract

Homomorphic encryption (HE), which allows computations on encrypted data, is an enabling technology for confidential cloud computing. One notable example is privacy-preserving Prediction-as-a-Service (PaaS), where machine-learning predictions are computed on encrypted data. However, developing HE-based solutions for encrypted PaaS is a tedious task which requires a careful design that predominantly depends on the deployment scenario and on leveraging the characteristics of modern HE schemes. Prior works on privacy-preserving PaaS focus solely on protecting the confidentiality of the client data uploaded to a remote model provider, e.g., a cloud offering a prediction API, and assume (or take advantage of the fact) that the model is held in plaintext. Furthermore, their aim is to either minimize the latency of the service by processing one sample at a time, or to maximize the number of samples processed per second, while processing a fixed (large) number of samples. In this work, we present slytHErin, an agile framework that enables privacy-preserving PaaS beyond the application scenarios considered in prior works. Thanks to its hybrid design leveraging HE and its multiparty variant (MHE), slytHErin enables novel PaaS scenarios by encrypting the data, the model or both. Moreover, slytHErin features a flexible input data packing approach that allows processing a batch of an arbitrary number of samples, and several computation optimizations that are model-and-setting-agnostic. slytHErin is implemented in Go and it allows end-users to perform encrypted PaaS on custom deep learning models comprising fully-connected, convolutional, and pooling layers, in a few lines of code and without having to worry about the cumbersome implementation and optimization concerns inherent to HE., Comment: Accepted for publication at 5th Workshop on Cloud Security and Privacy (Cloud S&P 2023)

Published
2023

7. Declaration of Computational Neurosurgery

Author

Di Ieva, Antonio, Suero Molina, Eric, Somerville, Margaret A., Beheshti, Amin, Staartjes, Victor E., Serra, Carlo, Theodore, Nicholas, Elliott, James M., Wesselink, Evert O., Russo, Carlo, Pilitsis, Julie G., Bennett, Christine C., Wu, Shandong, Hammond, Flora M., Lozano, Andres M., Cusimano, Michael D., Davidson, Jennilee M., Castellano, James F., Okonkwo, David O., Arefan, Dooman, Lee, Cheng-Chia, Zanier, Olivier, Da Mutten, Raffaele, Matula, Christian, Rutka, James T., Pease, Matthew, Liu, Sidong, Stummer, Walter, Matulionyte, Rita, Yang, Hongxi, Yuwen, Chang, Cheng, Xuelian, Fan, Hengwei, Wang, Xin, Ge, Zongyuan, Cepeda, Santiago, Sheehan, Jason P., Yang, Joseph Yuan-Mou, Hamer, Ryan P., Cohen-Gadol, Aaron, Hansford, Jordan R., Savage, Greg, Sowman, Paul F., Stewart, Caleb, Kateb, Babak, Sherif, Camillo, Perperidis, Antonios, Guller, Anna, Hanft, Simon, D’Amico, Randy S., Sav, Aydin, Cong, Cong, Song, Yang, Nicolosi, Federico, Wiedmann, Marcus K. H., Barone, Damiano G., Noorani, Imran, Magnussen, John, Krieg, Sandro M., Meling, Torstein R., De Ridder, Dirk, Lawton, Michael T., Rosenfeld, Jeffrey V., Crusio, Wim E., Series Editor, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, Rosenhouse-Dantsker, Avia, Editorial Board Member, Di Ieva, Antonio, editor, Suero Molina, Eric, editor, Liu, Sidong, editor, and Russo, Carlo, editor

Published
2024
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8. Privacy-Preserving Federated Recurrent Neural Networks

Author

Sav, Sinem, Diaa, Abdulrahman, Pyrgelis, Apostolos, Bossuat, Jean-Philippe, and Hubaux, Jean-Pierre

Subjects
Computer Science - Cryptography and Security
Abstract

We present RHODE, a novel system that enables privacy-preserving training of and prediction on Recurrent Neural Networks (RNNs) in a cross-silo federated learning setting by relying on multiparty homomorphic encryption. RHODE preserves the confidentiality of the training data, the model, and the prediction data; and it mitigates federated learning attacks that target the gradients under a passive-adversary threat model. We propose a packing scheme, multi-dimensional packing, for a better utilization of Single Instruction, Multiple Data (SIMD) operations under encryption. With multi-dimensional packing, RHODE enables the efficient processing, in parallel, of a batch of samples. To avoid the exploding gradients problem, RHODE provides several clipping approximations for performing gradient clipping under encryption. We experimentally show that the model performance with RHODE remains similar to non-secure solutions both for homogeneous and heterogeneous data distribution among the data holders. Our experimental evaluation shows that RHODE scales linearly with the number of data holders and the number of timesteps, sub-linearly and sub-quadratically with the number of features and the number of hidden units of RNNs, respectively. To the best of our knowledge, RHODE is the first system that provides the building blocks for the training of RNNs and its variants, under encryption in a federated learning setting., Comment: Accepted for publication at the 23rd Privacy Enhancing Technologies Symposium (PETS 2023)

Published
2022

15. POSEIDON: Privacy-Preserving Federated Neural Network Learning

Author

Sav, Sinem, Pyrgelis, Apostolos, Troncoso-Pastoriza, Juan R., Froelicher, David, Bossuat, Jean-Philippe, Sousa, Joao Sa, and Hubaux, Jean-Pierre

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

In this paper, we address the problem of privacy-preserving training and evaluation of neural networks in an $N$-party, federated learning setting. We propose a novel system, POSEIDON, the first of its kind in the regime of privacy-preserving neural network training. It employs multiparty lattice-based cryptography to preserve the confidentiality of the training data, the model, and the evaluation data, under a passive-adversary model and collusions between up to $N-1$ parties. To efficiently execute the secure backpropagation algorithm for training neural networks, we provide a generic packing approach that enables Single Instruction, Multiple Data (SIMD) operations on encrypted data. We also introduce arbitrary linear transformations within the cryptographic bootstrapping operation, optimizing the costly cryptographic computations over the parties, and we define a constrained optimization problem for choosing the cryptographic parameters. Our experimental results show that POSEIDON achieves accuracy similar to centralized or decentralized non-private approaches and that its computation and communication overhead scales linearly with the number of parties. POSEIDON trains a 3-layer neural network on the MNIST dataset with 784 features and 60K samples distributed among 10 parties in less than 2 hours., Comment: Accepted for publication at Network and Distributed Systems Security (NDSS) Symposium 2021

Published
2020

16. Scalable Privacy-Preserving Distributed Learning

Author

Froelicher, David, Troncoso-Pastoriza, Juan R., Pyrgelis, Apostolos, Sav, Sinem, Sousa, Joao Sa, Bossuat, Jean-Philippe, and Hubaux, Jean-Pierre

Subjects
Computer Science - Cryptography and Security
Abstract

In this paper, we address the problem of privacy-preserving distributed learning and the evaluation of machine-learning models by analyzing it in the widespread MapReduce abstraction that we extend with privacy constraints. We design SPINDLE (Scalable Privacy-preservINg Distributed LEarning), the first distributed and privacy-preserving system that covers the complete ML workflow by enabling the execution of a cooperative gradient-descent and the evaluation of the obtained model and by preserving data and model confidentiality in a passive-adversary model with up to N-1 colluding parties. SPINDLE uses multiparty homomorphic encryption to execute parallel high-depth computations on encrypted data without significant overhead. We instantiate SPINDLE for the training and evaluation of generalized linear models on distributed datasets and show that it is able to accurately (on par with non-secure centrally-trained models) and efficiently (due to a multi-level parallelization of the computations) train models that require a high number of iterations on large input data with thousands of features, distributed among hundreds of data providers. For instance, it trains a logistic-regression model on a dataset of one million samples with 32 features distributed among 160 data providers in less than three minutes., Comment: Published at the 21st Privacy Enhancing Technologies Symposium (PETS 2021)

Published
2020

17. Safety First: 2024's Safest States for Outdoor Workers

Author

Maive, Sav

Subjects
United States. Occupational Safety and Health Administration -- Safety and security measures, Safety regulations -- Safety and security measures, Work-related injuries -- Safety and security measures, Occupational health and safety -- Safety and security measures, Weather -- Safety and security measures, Insurance
Abstract

Which states take 'safety first' seriously for outdoor jobs? With the Occupational Safety and Health Administration's (OSHA) recently proposed rule for federal heat protections, Lawn Love ranked 2024's Safest States [...]

Published
2024

22. Opportunistic Candida Infections in Critical COVID-19 Patients

Author

Altinkaya Çavuş Mıne and Sav Hafıze

Subjects
opportunistic candida infections, covid-19, critical care, Genetics, QH426-470, Microbiology, QR1-502
Abstract

The frequency of opportunistic fungal infections in critically ill patients whose intensive care unit stays are prolonged due to coronavirus disease 2019 (COVID-19) is higher than in the period before COVID-19. We planned this study to improve the management of Candida infections by defining the Candida species, the etiology of infections caused by Candida species, and the antifungal susceptibility of the species. This retrospective study included patients older than 18 hospitalized in the intensive care unit (ICU) with a definitive diagnosis of COVID-19 for seven months (from March 2021 to September 2021). All study data that we recorded in a standard study form were analyzed with TURCOSA (Turcosa Analytics Ltd. Co., Turkey, www.turcosa.com.tr) statistical software. The patients were evaluated in four groups as group 1 (candidemia patients, n = 78), group 2 (candiduria patients, n = 189), group 3 (control patients, n = 57), and group 4 (patients with candidemia in urine cultures taken before Candida was detected in blood culture, n = 42). Candida species were identified using both conventional and VITEK® 2 (BioMérieux, France) methods. The antifungal susceptibility of fungi was determined using the E test method. Of the 5,583 COVID-19 patients followed during the study period, 78 developed candidemia, and 189 developed candiduria. The incidence of candidemia (per 1,000 admissions) was determined to be 1.6. As a result of statistical analysis, we found that Candida albicans was the dominant strain in candidemia and candiduria, and there was no antifungal resistance except for naturally resistant strains. Candida strains grown in blood and urine were the same in 40 of 42 patients. Mortality was 69.2% for group 1, 60.4% for group 2, and 57.8% for group 3. Antifungals were used in 34 (43.5%) patients from group 1, and 95 (50.2%) from group 2. In the candidemia group without antifungal use, mortality was quite high (77.2%). Antifungal use reduced mortality in the group 2 (p < 0.05). Length of ICU stays, comorbidity, broad-spectrum antibiotics, and corticosteroids are independent risk factors for candidemia in critically ill COVID-19 patients. Our study contributes to the knowledge of risk factors for developing COVID-19-related candida infections. The effect of candiduria on the development of candidemia in critically ill COVID-19 patients should be supported by new studies.

Published
2022
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23. How Emerging Adults Perceive Elements of Nature as Resources for Wellbeing: A Qualitative Photo-Elicitation Study

Author

Ernesta Sofija, Anne Cleary, Adem Sav, Bernadette Sebar, and Neil Harris

Subjects
nature, emerging adults, well-being, photo-elicitation, pathways, Urban groups. The city. Urban sociology, HT101-395
Abstract

Research that examines lived experience and how emerging adults seek to create wellbeing in their daily lives through nature is limited. This paper addresses this gap by providing unique insights into how emerging adults perceive and experience nature as a beneficial resource for their wellbeing. Data were collected using photo-elicitation interviews, where 18 emerging adults took photographs that represented their views on and experiences of wellbeing, and during the follow-up interviews discussed the meaning of their photographs. Without a priori mention, 14 participants identified contact with various elements of nature as important resources in supporting their wellbeing. It is the results of these 14 interviews that are discussed in this paper with a focus on (i) the elements of nature which these emerging adults identify as important resources for their wellbeing, (ii) experiences and the perceived pathways between these elements of nature and wellbeing. Thematic analysis revealed four distinct perceived pathways connecting nature to wellbeing, including symbiotic nurturing, building social glue, maintaining a positive outlook, and centreing yourself. Four elements of nature facilitated these pathways: domesticated fauna, domesticated flora, wild fauna and wild surrounding nature. The findings help build understanding of how emerging adults perceive elements of nature as resources for wellbeing and can inform the development of nature-oriented interventions.

Published
2022
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26. Human Detection for Night Surveillance using Adaptive Background Subtracted Image

Author

Khandhediya, Yash, Sav, Karishma, and Gajjar, Vandit

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Surveillance based on Computer Vision has become a major necessity in current era. Most of the surveillance systems operate on visible light imaging, but performance based on visible light imaging is limited due to some factors like variation in light intensity during the daytime. The matter of concern lies in the need for processing images in low light, such as in the need of nighttime surveillance. In this paper, we have proposed a novel approach for human detection using FLIR(Forward Looking Infrared) camera. As the principle involves sensing based on thermal radiation in the Near IR Region, it is possible to detect Humans from an image captured using a FLIR camera even in low light. The proposed method for human detection involves processing of Thermal images by using HOG (Histogram of Oriented Gradients) feature extraction technique along with some enhancements. The principle of the proposed technique lies in an adaptive background subtraction algorithm, which works in association with the HOG technique. By means of this method, we are able to reduce execution time, precision and some other parameters, which result in improvement of overall accuracy of the human detection system., Comment: 5 Pages, 7 Figures, 1 Table, National Conference on Advances in Computer Science Engineering & Technology

Published
2017

27. The role of personal protective equipment (PPE) in reducing firefighter exposure to chemical hazards: A systematic review.

Author

Chakr, Nicole and Sav, Adem

Abstract

This paper aims to investigate the effectiveness of personal protective equipment (PPE) in reducing firefighter exposure to various hazardous chemicals from the smoke emitted during fires. A systematic review of peer-reviewed articles was undertaken utilizing five databases: Medline, Embase, Web of Science, Scopus, and CINHAL. Studies published between 2013 and 2023 that investigated the effectiveness of PPE in reducing firsthand exposure to at least one chemical were included. Extracted data were grouped into two overarching themes related to PPE: (a) Respiratory Protection and (b) Personal Protective Clothing (PPC). Overall, 21 studies met the inclusion criteria and were considered for further analysis. Respiratory protection, particularly self-contained breathing apparatus (SCBA), offered the most protection in preventing inhalation exposure to chemical hazards. There was limited evidence on the effectiveness of firefighter turnout gear in reducing skin contamination. Combustion contaminants, especially highly volatile compounds like benzene, were found to permeate and penetrate through and around the protective clothing. In conclusion, certain respirators, particularly SCBA, provided the best protection against inhalation exposure to chemicals; however, PPC did not appear to provide complete protection, particularly against the more volatile chemicals like benzene. [ABSTRACT FROM AUTHOR]

Published
2024
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29. 1 dB per Floor? How Does Noise and Vibration Propagate in High-Rise Buildings Near Railway Lines?

Author

Anderson, Dave, Shimada, Sav, Hanson, David, Hirschel, Ernst Heinrich, Founding Editor, Schröder, Wolfgang, Series Editor, Boersma, Bendiks Jan, Editorial Board Member, Fujii, Kozo, Editorial Board Member, Haase, Werner, Editorial Board Member, Leschziner, Michael A., Editorial Board Member, Periaux, Jacques, Editorial Board Member, Pirozzoli, Sergio, Editorial Board Member, Rizzi, Arthur, Editorial Board Member, Roux, Bernard, Editorial Board Member, Shokin, Yurii I., Editorial Board Member, Mäteling, Esther, Managing Editor, Degrande, Geert, editor, Lombaert, Geert, editor, Anderson, David, editor, de Vos, Paul, editor, Gautier, Pierre-Etienne, editor, Iida, Masanobu, editor, Nelson, James Tuman, editor, Nielsen, Jens C. O., editor, Thompson, David J., editor, Tielkes, Thorsten, editor, and Towers, David A., editor

Published
2021
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30. Insider Threat Detection Based on Anomalous Behavior of User for Cybersecurity

Author

Sav, Ujwala, Magar, Ganesh, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Jat, Dharm Singh, editor, Shukla, Samiksha, editor, Unal, Aynur, editor, and Mishra, Durgesh Kumar, editor

Published
2021
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31. Risk factors and lethality associated with Candidemia in severe COVID-19 patients

Author

Zehra Beştepe Dursun, Hilal Sipahioğlu, Recep Civan Yüksel, Hafize Sav, and Ilhami Çelik

Subjects
covid-19, candidemia, intensive care unit, risk factor, Internal medicine, RC31-1245, Biology (General), QH301-705.5
Abstract

Background and Purpose: Candidemia remained important in the intensive care units(ICU) during the COVID-19 pandemic. This study aimed to investigate the clinical and laboratory data on candidemia in COVID-19 patients.Materials and Methods: The baseline characteristics, as well as laboratory and clinicalfindings of candidemia and non-candidemia patients, were compared. Candidemia was defined as the isolation of Candida spp. from blood cultures. The isolates were identified by VITEK® 2 (bioMérieux, France) commercial method. Antifungal susceptibility was assessed using the E-test method. Univariate and multiple binary logistic regression analyses were performed to compare the variables.Results: In total, 126 patients with the COVID-19 disease were included. Candidemiawas diagnosed in 44 (35%) of the patients. The number of patients with diabetes mellitus and chronic renal failure was higher in the candidemia group. In the candidemia group, the duration of ICU stay of patients, the 30-day mortality rate, mechanical ventilation therapy, and systemic corticosteroids (Prednisone) usage were significantly higher in candidemia patients. Moreover, the median white blood cell, neutrophils, and lactate dehydrogenase were higher in the candidemia group. Univariate and multiple binary logistic regression analyses were performed to compare the variables. Isolated species were identified as Candida albicans (n=12, 41%), Candida parapsilosis (n=7, 24%), Candida glabrata (n=6, 21%), Candida tropicalis (n=3, 10%), and Candida dublinensis (n=1, 3%). In total, three isolates of six C. glabrata species had dose-dependent sensitivity to fluconazole, and one C. parapsilosis was determined to be resistant.Conclusion: The COVID-19 patients who are admitted to ICU have many risk factors associated with candidemia. The most common risk factors for the development of candidemia were mechanical ventilation, diabetes mellitus, neutrophilia, and low hemoglobin level. The most frequently isolated species was C. albicans. Moreover, caspofungin was found to be the most effective drug in vitro. No significant resistancepattern was detected against the isolated species. It should be noted that risk-stratified antifungal prophylaxis in the ICU is possible.

Published
2022
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35. How Does 'Stay Home' Transform a House? The Route Map of a Research

Author

Armağan Seçil Melikoğlu Eke, Derya Adıgüzel Özbek, Gülay Usta, Özge Ilık Saltık, Sedef Sav, Elif Gelmez Demir, and Furkan Evliyaoğlu

Subjects
Covid-19 pandemic, housing, research design, quantitative research, qualitative research, Architecture, NA1-9428, City planning, HT165.5-169.9
Abstract

COVID-19 pandemic caused transformation by influencing the physical and psycho-social status of houses, and by introducing different functions and needs which led to or will lead to changes in individuals’ expectations from their houses. Drawing on this idea, this study allows for the detection of such changes through examination and for the consideration of future house arrangements, housing designs and their production by identifying the usage possibilities of existing houses. The research design is structured in three main steps. First step is the literature part that draws the conceptual framework of the study. Second step includes survey technique with use of panel design as a quantitative research method. In the research, third step has built with semi-structured interview to be deepen analyzing of the results of the quantitative part. The findings reached through this study have the potential to lead future house arrangements as well as housing production and design which are also significant in terms of innovative and creative housing designs studied within disciplines such as interior architecture and architecture. Sample of the research is the city of Istanbul which is first of the most affected cities from COVID-19 pandemic. Selecting a big and multi-component metropolis like Istanbul as research area for residential spaces brought different difficulties in the application processes of research methods while allowing the multidimensional examination of the subject. The research design proposed by this study possess the quality of a guiding sample for future scientific studies.

Published
2022
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36. Patient and physician perspectives on treatment burden in end-stage kidney disease: a nominal group technique study

Author

Claudia C Dobler, Rae Thomas, Magnolia Cardona, Adem Sav, Sarah T Thomas, Zoe Michaleff, and Thomas T Titus

Subjects
Medicine
Abstract

Objectives The treatment workload associated with end-stage kidney disease (ESKD) is high. The treatment burdens experienced by patients with ESKD are not well understood. In this study, we aimed to elucidate the most important areas of treatment burden for discussion in a clinical encounter from the perspectives of patients with ESKD and nephrologists. We sought to explore possible solutions to these high priority treatment burden challenges.Design Nominal group technique (NGT) sessions.Setting and participants Three in-person NGT sessions were conducted with 19 patients with dialysis-dependent ESKD from one tertiary treatment centre (mean age 64 years; range 47–82). All patients were either retired or on a disability pension; 74% perceived moderate or severe treatment burden; and 90% spent more than 11 hours on treatment-related activities per week (range 11–30). One online NGT session was conducted with six nephrologists from two Australian states.Main outcome measures The primary outcome was a ranked list of treatment burden priorities. The secondary outcome was potential solutions to these treatment burden challenges.Results Every patient group ranked health system issues as the most important treatment burden priority. This encompassed lack of continuity and coordination of care, dissatisfaction with frequent healthcare encounters and challenges around healthcare access. Psychosocial burdens on patients and families were perceived to be the most important area of treatment burden by physicians, and were ranked the second highest priority by patients.Conclusions Discussing treatment burden in a clinical encounter may lead to a better understanding of patients’ capacity to cope with their treatment workload. This could facilitate tailored care, improve health outcomes, treatment sustainability and patients’ overall quality of life.

Published
2022
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40. Selling “Health”, Selling Immortality: Constructing Illness & Wellness Narratives Within Online Biohacking Communities

Author

Pérez, Emma, Bose, Dev K., Rains, Steve, Schlauderaff, Sav, Pérez, Emma, Bose, Dev K., Rains, Steve, and Schlauderaff, Sav

Abstract

The wellness industry tells us as consumers that it is our moral imperative to strive for “health”, and simultaneously aims to sell us products to try to achieve this reality that is always out of reach. Biohacking presents us with the question of, if we could take control of our bodyminds to reach these goals, would we? Biohacking is generally defined as the science, and sometimes art, of optimizing our bodies and minds through the use of technology. These technological interventions range from diet and lifestyle changes, to supplements, wearable self-tracking devices, sauna bathing and cryotherapy, to more “extreme” examples of injecting microchips, gene editing, or the use of blood transfusions in the aims of decreasing one’s biological age. These technologies utilized by biohackers require critical engagement, and discernment around the future of “health” they are creating Within my dissertation, Selling “Health”, Selling Immortality, I center my analysis on online biohacking communities to identify how illness and wellness narratives are constructed, and then utilized to market biohacking products. I have selected four high-profile biohackers located within the United States: Dave Asprey, David Sinclair, Ellen Jorgensen, and Josie Zayner, along with their companies from 2012-2024 as the scope of my project. Analysis of media and research articles published about these selected biohackers was performed; and then compared to a branding analysis of their social media accounts, websites, podcasts, and documentaries. Throughout the dissertation, I return to the question of how “health,” illness, and disability are discussed and represented within online biohacking communities; and what role ableism, healthism, fatphobia, class, white supremacy, and hyper-masculinity play in the branding of mainstream biohackers in the United States. From my data analysis of these four biohackers, I engaged with biohacking experiments on my own bodymind for a year, and documented thi

Published
2024

41. Microsurgical management of midbrain gliomas: surgical results and long-term outcome in a large, single-surgeon, consecutive series

Author

Serra, Carlo; https://orcid.org/0000-0002-7305-550X, Türe, Hatice, Fırat, Zeynep, Staartjes, Victor E; https://orcid.org/0000-0003-1039-2098, Yaltırık, Cumhur Kaan, Ekinci, Gazanfer, Sav, Aydin, Türe, Uğur; https://orcid.org/0000-0002-7449-6171, Serra, Carlo; https://orcid.org/0000-0002-7305-550X, Türe, Hatice, Fırat, Zeynep, Staartjes, Victor E; https://orcid.org/0000-0003-1039-2098, Yaltırık, Cumhur Kaan, Ekinci, Gazanfer, Sav, Aydin, and Türe, Uğur; https://orcid.org/0000-0002-7449-6171

Abstract

OBJECTIVE The authors report on a large, consecutive, single-surgeon series of patients undergoing microsurgical removal of midbrain gliomas. Emphasis is put on surgical indications, technique, and results as well as long-term oncological follow-up. METHODS A retrospective analysis was performed of prospectively collected data from a consecutive series of patients undergoing microneurosurgery for midbrain gliomas from March 2006 through June 2022 at the authors' institution. According to the growth pattern and location of the lesion in the midbrain (tegmentum, central mesencephalic structures, and tectum), one of the following approaches was chosen: transsylvian (TS), extreme anterior interhemispheric transcallosal (eAIT), posterior interhemispheric transtentorial subsplenial (PITS), paramedian supracerebellar transtentorial (PST), perimedian supracerebellar (PeS), perimedian contralateral supracerebellar (PeCS), and transuvulotonsillar fissure (TUTF). Clinical and radiological data were gathered according to a standard protocol and reported according to common descriptive statistics. The main outcomes were rate of gross-total resection; extent of resection; occurrence of any complications; variation in Karnofsky Performance Status score at discharge, 3 months, and last follow-up; progression-free survival (PFS); and overall survival (OS). RESULTS Fifty-four patients (28 of them pediatric) met the inclusion criteria (6 with high-grade and 48 with low-grade gliomas [LGGs]). Twenty-two tumors were in the tegmentum, 7 in the central mesencephalic structures, and 25 in the tectum. In no instance did the glioma originate in the cerebral peduncle. TS was performed in 2 patients, eAIT in 6, PITS in 23, PST in 16, PeS in 4, PeCS in 1, and TUTF in 2 patients. Gross-total resection was achieved in 39 patients (72%). The average extent of resection was 98.0% (median 100%, range 82%-100%). There were no deaths due to surgery. Nine patients experienced transient and 2 patients e

Published
2024

43. The Relationship Between Clinical Phenotypes and Chromosomal Microdeletions/Duplications in Pediatric Neurology

Author

Esra Habiloğlu, Nadide Melike Sav, Recep Eröz, and Sevim Türay

Subjects
chromosomal microarray analysis, pediatric neurology, myelination delay, hypotonia, global developmental delay, intellectual disability, kromozomal mikrodizi analizi, pediatrik nöroloji, miyelinizasyon geriliği, hipotoni, global gelişme geriliği, zihinsel yetersizlik, Medicine, Medicine (General), R5-920
Abstract

Aim: The aim of this study was to determine the diagnostic utility of chromosomal microarray analysis (CMA) in daily pediatric neurology practice and to identify the guiding clinical parameters for patients requiring this test. Material and Methods: The CMA results for 91 patients with global developmental delay/intellectual disability (GDD/ID) admitted to our pediatric neurology clinic for various reasons between 2018 and 2020 were examined. Demographical and clinical data for 34 patients (37.4%) in whom del/dup was determined at CMA and 57 patients (62.6%) with normal CMA were compared. Results: There was no statistically significant difference between two groups in terms of demographic characteristics such as age, gender, type of delivery, gestational age, etc. Dysmorphisms, hypotonia, myelination abnormalities were significantly more frequent in patients with del/dup than in patients with normal result. The frequency of macrocephaly and obesity was higher in the normal group, and that of generalized seizures was higher among epileptic patients in this group. Nineteen (55.9%) of the 34 cases who have del/dup detected at analysis were regarded as pathogenic, 15 (44.1%) as uncertain clinical significance (likely pathogenic, likely benign and no subclassification). Conclusion: Since CMA is an expensive, laborious, and time-consuming test, considering clinical parameters when requesting CMA will yield high diagnostic efficiency. A high possibility of copy number variants may be predicted in GDD/ID patients with dysmorphisms, hypotonia, and myelination delay. CMA should represent the genetic analysis of choice in pediatric neurology practice in case of no finding suggesting a different etiology in these patients.

Published
2021
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46. Refugee and asylum‐seeker children and health problems in the city of Duzce, Türkiye.

Author

Cakmak, Hatice Mine, Kocabay, Kenan, Temizkan, Ramazan Cahit, Turay, Sevim, Ozde, Sukriye, Kurt, Fatih, Sav, Nadide Melike, Erguven, Muferet, and Coşkun, Emel

Subjects
CHILDREN'S health, IMMIGRANTS, ANEMIA, ACADEMIC medical centers, MALNUTRITION, HEALTH insurance, QUESTIONNAIRES, INFECTION, DESCRIPTIVE statistics, PEDIATRICS, QUALITY assurance, MEDICAL needs assessment, DATA analysis software, CHILD care, REFUGEES, CHILDREN
Abstract

Introduction: This study examines the health problems and healthcare needs of refugee and asylum‐seeker children and aims to develop strategies for improvement. Methods: Based on quantitative data from 448 refugee and asylum‐seeker children and 222 non‐refugee local children, this study was conducted at Düzce University, Department of Paediatrics, between 2010 and 2021. The refugee children originated from three countries: Iraq (n = 304), Syria (n = 101) and Afghanistan (n = 43). The data were analysed using the SPSS data analysis program. Ethical clearance was obtained from the Ethics Committee of Düzce Üniversity. Results: The results suggest that refugee and asylum‐seeker children have significantly higher rates of acute illness or infection, malnutrition (p < 0.001) and anaemia (p < 0.001) than local children as a result of living in overcrowded families (p = 0.017) and unhealthy conditions. Adolescent pregnancy (p = 0.049) emerges as an important social problem as a result of child marriage among refugee children, mostly in the form of consanguineous marriages (p < 0.001). The rate of having at least two adolescent pregnancies (under 18) was highest among Syrian refugee girls (p = 0.01). Although refugee and asylum‐seeker children have higher rates of health insurance (between 74% and 95%), they have lower rates of insurance compared to local children. This research also compares the data from three nationalities, including Syria, Afghanistan and Iraq children; Iraqi and Afghan children under the international protection (IP) system with limited social support and rights had worse health conditions compared to other groups. Although Iraqi children had the highest rates of health insurance on admission (p < 0.001), they also had higher rates of chronic diseases (p = 0.001), infections (p = 0.004), allergic rhinitis (p = 0.001) and malnutrition (p < 0.001). The youngest age of admission (p = 0.006) and the shortest length of stay (p = 0.004) were for Afghan children who also had higher rates of upper respiratory infections (p = 0.021). Conclusions: This study highlights the urgent need for improved screening programmes and the importance of collaborative efforts to address the specific health needs of these populations. Addressing the health status of child refugees is a complex and multifaceted task that requires the active participation of healthcare professionals, policymakers and researchers, each of whom has a crucial role to play. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Factors associated with suicide attempts among Australian transgender adults

Author

Sav Zwickl, Alex Fang Qi Wong, Eden Dowers, Shalem Yiner-Lee Leemaqz, Ingrid Bretherton, Teddy Cook, Jeffrey D. Zajac, Paul S. F. Yip, and Ada S. Cheung

Subjects
Transgender, Mental health, Suicide, Depression, Psychiatry, RC435-571
Abstract

Abstract Background Transgender, including gender diverse and non-binary people, henceforth referred to collectively as trans people, are a highly marginalised population with alarming rates of suicidal ideation, attempted suicide and self-harm. We aimed to understand the risk and protective factors of a lifetime history of attempted suicide in a community sample of Australian trans adults to guide better mental health support and suicide prevention strategies. Methods Using a non-probability snowball sampling approach, a total of 928 trans adults completed a cross-sectional online survey between September 2017 and January 2018. The survey assessed demographic data, mental health morbidity, a lifetime history of intentional self-harm and attempted suicide, experiences of discrimination, experiences of assault, access to gender affirming healthcare and access to trans peer support groups. Logistic regression was used to examine the risk or protective effect of participant characteristics on the odds of suicide. Results Of 928 participants, 85% self-reported a lifetime diagnosis of depression, 63% reported previous self-harm, and 43% had attempted suicide. Higher odds of reporting a lifetime history of suicide attempts were found in people who were; unemployed (adjusted odds ratio (aOR) 1.55 (1.05, 2.29), p = 0.03), had a diagnosis of depression (aOR 3.70 (2.51, 5.45), p

Published
2021
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48. Women’s empowerment and child growth faltering in Ethiopia: evidence from the Demographic and Health Survey

Author

Alemayehu Gonie Mekonnen, Daniel Bogale Odo, Dabere Nigatu, Adem Sav, and Kiya Kedir Abagero

Subjects
Women’s empowerment, Child growth faltering, EDHS, Gynecology and obstetrics, RG1-991, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Despite numerous national and international efforts to alleviate child growth faltering, it remains a global health challenge. There is a growing body of literature that recognizes the importance of women’s empowerment in a wide range of public health topics, such as the utilization of maternal healthcare services, agricultural productivity, and child nutrition. However, in Ethiopia, the relationship between women’s empowerment and child nutritional status is not studied at the national level. This study aimed to determine the association between women’s empowerment and growth faltering in under-5 children in Ethiopia. Methods The data source for this analysis is the 2016 Ethiopian Demographic and Health Survey (EDHS): a nationally representative household survey on healthcare. The EDHS employed a two-stage stratified cluster sampling technique. We computed standard women’s empowerment indices, following the Survey-based Women’s emPowERment index approach. A multilevel logistic regression model that accounted for cluster-level random effects was used to estimate the association between women’s empowerment and child growth faltering (stunting, wasting and underweight). Results Attitude to violence, social independence, and decision-making were the three domains of women’s empowerment that were associated with child growth faltering. One standard deviation increase in each domain of empowerment was associated with a reduction in the odds of stunting: attitude towards violence (AOR = 0.92; 95% CI 0.88–0.96; p

Published
2021
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50. Privacy-preserving federated neural network learning for disease-associated cell classification

Author

Sinem Sav, Jean-Philippe Bossuat, Juan R. Troncoso-Pastoriza, Manfred Claassen, and Jean-Pierre Hubaux

Subjects
DSML 3: Development/pre-production: Data science output has been rolled out/validated across multiple domains/problems, Computer software, QA76.75-76.765
Abstract

Summary: Training accurate and robust machine learning models requires a large amount of data that is usually scattered across data silos. Sharing or centralizing the data of different healthcare institutions is, however, unfeasible or prohibitively difficult due to privacy regulations. In this work, we address this problem by using a privacy-preserving federated learning-based approach, PriCell, for complex models such as convolutional neural networks. PriCell relies on multiparty homomorphic encryption and enables the collaborative training of encrypted neural networks with multiple healthcare institutions. We preserve the confidentiality of each institutions’ input data, of any intermediate values, and of the trained model parameters. We efficiently replicate the training of a published state-of-the-art convolutional neural network architecture in a decentralized and privacy-preserving manner. Our solution achieves an accuracy comparable with the one obtained with the centralized non-secure solution. PriCell guarantees patient privacy and ensures data utility for efficient multi-center studies involving complex healthcare data. The bigger picture: High-quality medical machine learning models will benefit greatly from collaboration between health care institutions. Yet, it is usually difficult to transfer data between these institutions due to strict privacy regulations. In this study, we propose a solution, PriCell, that relies on multiparty homomorphic encryption to enable privacy-preserving collaborative machine learning while protecting via encryption the institutions' input data, the model, and any value exchanged between the institutions. We show the maturity of our solution by training a published state-of-the-art convolutional neural network in a decentralized and privacy-preserving manner. We compare the accuracy achieved by PriCell with the centralized and non-secure solutions and show that PriCell guarantees privacy without reducing the utility of the data. The benefits of PriCell constitute an important landmark for real-world applications of collaborative training while preserving privacy.

Published
2022
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