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1,164 results on '"Banerjee, Rajarshi"'

2. The Effect of Multi-Parametric Magnetic Resonance Imaging in Standard of Care for Nonalcoholic Fatty Liver Disease: Protocol for a Randomized Control Trial

Author

Tonev, Dimitar, Shumbayawonda, Elizabeth, Tetlow, Louise Ann, Herdman, Laura, French, Marika, Rymell, Soubera, Thomaides-Brears, Helena, Caseiro-Alves, Filipe, Castelo-Branco, Miguel, Ferreira, Carlos, Coenraad, Minneke, Lamb, Hildo, Beer, Meinrad, Kelly, Matt, Banerjee, Rajarshi, and Dollinger, Matthias

Subjects
Medicine, Computer applications to medicine. Medical informatics, R858-859.7
Abstract

BackgroundThe rising prevalence of nonalcoholic fatty liver disease (NAFLD) and the more aggressive subtype, nonalcoholic steatohepatitis (NASH), is a global public health concern. Left untreated, NAFLD/NASH can lead to cirrhosis, liver failure, and death. The current standard for diagnosing and staging liver disease is a liver biopsy, which is costly, invasive, and carries risk for the patient. Therefore, there is a growing need for a reliable, feasible, and cost-effective, noninvasive diagnostic tool for these conditions. LiverMultiScan is one such promising tool that uses multi-parametric magnetic resonance imaging (mpMRI) to characterize liver tissue and to aid in the diagnosis and monitoring of liver diseases of various etiologies. ObjectiveThe primary objective of this trial (RADIcAL1) is to evaluate the cost-effectiveness of the introduction of LiverMultiScan as a standardized diagnostic test for liver disease in comparison to standard care for NAFLD, in different EU territories. MethodsRADIcAL1 is a multi-center randomized control trial with 2 arms conducted in 4 European territories (13 sites, from across Germany, Netherlands, Portugal, and the United Kingdom). In total, 1072 adult patients with suspected fatty liver disease will be randomized to be treated according to the result of the mpMRI in the intervention arm, so that further diagnostic evaluation is recommended only when values for metrics of liver fat or fibro-inflammation are elevated. Patients in the control arm will be treated as per center guidelines for standard of care. The primary outcome for this trial is to compare the difference in the proportion of patients with suspected NAFLD incurring liver-related hospital consultations or liver biopsies between the study arms, from the date of randomization to the end of the study follow-up. Secondary outcomes include patient feedback from a patient satisfaction questionnaire, at baseline and all follow-up visits to the end of the study, and time, from randomization to diagnosis by the physician, as recorded at the final follow-up visit. ResultsThis trial is currently open for recruitment. The anticipated completion date for the study is December 2020. ConclusionsThis randomized controlled trial will provide the evidence to accelerate decision making regarding the inclusion of mpMRI-based tools in existing NAFLD/NASH clinical care. RADIcAL1 is among the first and largest European health economic studies of imaging technologies for fatty liver disease. Strengths of the trial include a high-quality research design and an in-depth assessment of the implementation of the cost-effectiveness of the mpMRI diagnostic. If effective, the trial may highlight the health economic burden on tertiary-referral hepatology clinics imposed by unnecessary consultations and invasive diagnostic investigations, and demonstrate that including LiverMultiScan as a NAFLD diagnostic test may be cost-effective compared to liver-related hospital consultations or liver biopsies. Trial RegistrationClinicalTrials.gov NCT03289897 https://clinicaltrials.gov/ct2/show/NCT03289897 International Registered Report Identifier (IRRID)DERR1-10.2196/19189

Published
2020
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8. Clonal haematopoiesis and risk of chronic liver disease.

Author

Dichtel, Laura, Griffin, Gabriel, Uddin, Md, Gibson, Christopher, Kovalcik, Veronica, Lin, Amy, McConkey, Marie, Vromman, Amelie, Sellar, Rob, Kim, Peter, Agrawal, Mridul, Weinstock, Joshua, Long, Michelle, Yu, Bing, Banerjee, Rajarshi, Nicholls, Rowan, Dennis, Andrea, Kelly, Matt, Loh, Po-Ru, McCarroll, Steve, Boerwinkle, Eric, Vasan, Ramachandran, Jaiswal, Siddhartha, Johnson, Andrew, Chung, Raymond, Corey, Kathleen, Levy, Daniel, Ballantyne, Christie, Ebert, Benjamin, Natarajan, Pradeep, Wong, Waihay, Emdin, Connor, Bick, Alexander, Zekavat, Seyedeh, Niroula, Abhishek, and Pirruccello, James

Subjects
Animals, Mice, Clonal Hematopoiesis, Hepatitis, Inflammation, Liver Cirrhosis, Non-alcoholic Fatty Liver Disease, Disease Susceptibility, Odds Ratio, Disease Progression
Abstract

Chronic liver disease is a major public health burden worldwide1. Although different aetiologies and mechanisms of liver injury exist, progression of chronic liver disease follows a common pathway of liver inflammation, injury and fibrosis2. Here we examined the association between clonal haematopoiesis of indeterminate potential (CHIP) and chronic liver disease in 214,563 individuals from 4 independent cohorts with whole-exome sequencing data (Framingham Heart Study, Atherosclerosis Risk in Communities Study, UK Biobank and Mass General Brigham Biobank). CHIP was associated with an increased risk of prevalent and incident chronic liver disease (odds ratio = 2.01, 95% confidence interval (95% CI) [1.46, 2.79]; P

Published
2023

21. Highly Complex Magnetic Structures Resulting From Hierarchical Phase Separation in AlCo(Cr)FeNi High Entropy Alloys

Author

Lan, Qianqian, Kovács, András, Caron, Jan, Du, Hongchu, Song, Dongsheng, Dasari, Sriswaroop, Gwalani, Bharat, Chaudhary, Varun, Ramanujan, Raju V., Banerjee, Rajarshi, and Dunin-Borkowski, Rafal E.

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

Magnetic high entropy alloys (HEAs) are a new category of high-performance magnetic materials, with multi-component concentrated compositions and complex multi-phase structures. Although there have been numerous reports of their interesting magnetic properties, there is very limited understanding about the interplay between their hierarchical multi-phase structures and their local magnetic structures. By employing high spatial resolution correlative magnetic, structural and chemical studies, we reveal the influence of a hierarchically decomposed B2 + A2 structure in an AlCo0.5Cr0.5FeNi HEA on the formation of magnetic vortex states within individual A2 (disordered BCC) precipitates, which are distributed in an ordered B2 matrix that is weakly ferromagnetic. Non-magnetic or weakly ferromagnetic B2 precipitates in large magnetic domains of the A2 phase, and strongly magnetic Fe-Co-rich interphase A2 regions, are also observed. These results provide important insight into the origin of coercivity in this HEA, which can be attributed to a complex magnetization process that includes the successive reversal of magnetic vortices.

Published
2021

22. Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm

Author

Dukkipati, Ambedkar, Banerjee, Rajarshi, Ayyagari, Ranga Shaarad, and Udaybhai, Dhaval Parmar

Subjects
Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract

Solving complex problems using reinforcement learning necessitates breaking down the problem into manageable tasks and learning policies to solve these tasks. These policies, in turn, have to be controlled by a master policy that takes high-level decisions. Hence learning policies involves hierarchical decision structures. However, training such methods in practice may lead to poor generalization, with either sub-policies executing actions for too few time steps or devolving into a single policy altogether. In our work, we introduce an alternative approach to learn such skills sequentially without using an overarching hierarchical policy. We propose this method in the context of environments where a major component of the objective of a learning agent is to prolong the episode for as long as possible. We refer to our proposed method as Sequential Soft Option Critic. We demonstrate the utility of our approach on navigation and goal-based tasks in a flexible simulated 3D navigation environment that we have developed. We also show that our method outperforms prior methods such as Soft Actor-Critic and Soft Option Critic on various environments, including the Atari River Raid environment and the Gym-Duckietown self-driving car simulator., Comment: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): 2022

Published
2021

23. Impact of Interventional Policies Including Vaccine on Covid-19 Propagation and Socio-Economic Factors

Author

Wu, Haonan, Banerjee, Rajarshi, Venkatachalam, Indhumathi, Percy-Hughes, Daniel, and Chougale, Praveen

Subjects
Computer Science - Machine Learning, Statistics - Applications
Abstract

A novel coronavirus disease has emerged (later named COVID-19) and caused the world to enter a new reality, with many direct and indirect factors influencing it. Some are human-controllable (e.g. interventional policies, mobility and the vaccine); some are not (e.g. the weather). We have sought to test how a change in these human-controllable factors might influence two measures: the number of daily cases against economic impact. If applied at the right level and with up-to-date data to measure, policymakers would be able to make targeted interventions and measure their cost. This study aims to provide a predictive analytics framework to model, predict and simulate COVID-19 propagation and the socio-economic impact of interventions intended to reduce the spread of the disease such as policy and/or vaccine. It allows policymakers, government representatives and business leaders to make better-informed decisions about the potential effect of various interventions with forward-looking views via scenario planning. We have leveraged a recently launched open-source COVID-19 big data platform and used published research to find potentially relevant variables (features) and leveraged in-depth data quality checks and analytics for feature selection and predictions. An advanced machine learning pipeline has been developed armed with a self-evolving model, deployed on a modern machine learning architecture. It has high accuracy for trend prediction (back-tested with r-squared) and is augmented with interpretability for deeper insights.

Published
2021

25. Clonal haematopoiesis and risk of chronic liver disease

Author

Wong, Waihay J., Emdin, Connor, Bick, Alexander G., Zekavat, Seyedeh M., Niroula, Abhishek, Pirruccello, James P., Dichtel, Laura, Griffin, Gabriel, Uddin, Md Mesbah, Gibson, Christopher J., Kovalcik, Veronica, Lin, Amy E., McConkey, Marie E., Vromman, Amelie, Sellar, Rob S., Kim, Peter G., Agrawal, Mridul, Weinstock, Joshua, Long, Michelle T., Yu, Bing, Banerjee, Rajarshi, Nicholls, Rowan C., Dennis, Andrea, Kelly, Matt, Loh, Po-Ru, McCarroll, Steve, Boerwinkle, Eric, Vasan, Ramachandran S., Jaiswal, Siddhartha, Johnson, Andrew D., Chung, Raymond T., Corey, Kathleen, Levy, Daniel, Ballantyne, Christie, Ebert, Benjamin L., and Natarajan, Pradeep

Published
2023
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26. R&G Tech Studio Presents: Venture Capital And Emerging Companies Partner Raj Banerjee (Podcast)

Author

Banerjee, Rajarshi

Subjects
Artificial intelligence -- Usage -- Forecasts and trends, Business enterprises -- Finance -- Forecasts and trends -- Technology application, Venture capital companies -- Investments, Company financing, Market trend/market analysis, Artificial intelligence, Technology application, Company investment, Business, international
Abstract

On this episode of the R&G Tech Studio podcast, host Brad Flint, co-leader of Ropes & Gray's venture capital and emerging companies practice, is joined by Raj Banerjee, a partner [...]

Published
2024

27. Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS): Assessment & validation of imaging modality performance across the NAFLD spectrum in a prospectively recruited cohort study (the LITMUS imaging study): Study protocol

Author

Pavlides, Michael, Mózes, Ferenc E., Akhtar, Salma, Wonders, Kristy, Cobbold, Jeremy, Tunnicliffe, Elizabeth M., Allison, Michael, Godfrey, Edmund M., Aithal, Guruprasad P., Francis, Susan, Romero-Gomez, Manuel, Castell, Javier, Fernandez-Lizaranzu, Isabel, Aller, Rocio, González, Rebeca Sigüenza, Agustin, Salvador, Pericàs, Juan M., Boursier, Jerome, Aube, Christophe, Ratziu, Vlad, Wagner, Mathilde, Petta, Salvatore, Antonucci, Michela, Bugianesi, Elisabetta, Faletti, Riccardo, Miele, Luca, Geier, Andreas, Schattenberg, Jörn M., Tilman, Emrich, Ekstedt, Mattias, Lundberg, Peter, Berzigotti, Annalisa, Huber, Adrian T., Papatheodoridis, George, Yki-Järvinen, Hannele, Porthan, Kimmo, Schneider, Moritz Jörg, Hockings, Paul, Shumbayawonda, Elizabeth, Banerjee, Rajarshi, Pepin, Kay, Kalutkiewicz, Mike, Ehman, Richard L., Trylesinksi, Aldo, Coxson, Harvey O., Martic, Miljen, Yunis, Carla, Tuthill, Theresa, Bossuyt, Patrick M., Anstee, Quentin M., Neubauer, Stefan, and Harrison, Stephen

Published
2023
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31. Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis

Author

Anstee, Quentin M, Daly, Ann K, Govaere, Olivier, Cockell, Simon, Tiniakos, Dina, Bedossa, Pierre, Burt, Alastair, Oakley, Fiona, Cordell, Heather J, Day, Christopher P, Wonders, Kristy, Missier, Paolo, McTeer, Matthew, Vale, Luke, Oluboyede, Yemi, Breckons, Matt, Bossuyt, Patrick M, Zafarmand, Hadi, Vali, Yasaman, Lee, Jenny, Nieuwdorp, Max, Holleboom, Adriaan G, Verheij, Joanne, Ratziu, Vlad, Clément, Karine, Patino-Navarrete, Rafael, Pais, Raluca, Paradis, Valerie, Schuppan, Detlef, Schattenberg, Jörn M, Surabattula, Rambabu, Myneni, Sudha, Straub, Beate K, Vidal-Puig, Toni, Vacca, Michele, Rodrigues-Cuenca, Sergio, Allison, Mike, Kamzolas, Ioannis, Petsalaki, Evangelia, Campbell, Mark, Lelliott, Chris J, Davies, Susan, Orešič, Matej, Hyötyläinen, Tuulia, McGlinchey, Aiden, Mato, Jose M, Millet, Óscar, Dufour, Jean-François, Berzigotti, Annalisa, Masoodi, Mojgan, Pavlides, Michael, Harrison, Stephen, Neubauer, Stefan, Cobbold, Jeremy, Mozes, Ferenc, Akhtar, Salma, Olodo-Atitebi, Seliat, Banerjee, Rajarshi, Kelly, Matt, Shumbayawonda, Elizabeth, Dennis, Andrea, Andersson, Anneli, Wigley, Ioan, Romero-Gómez, Manuel, Gómez-González, Emilio, Ampuero, Javier, Castell, Javier, Gallego-Durán, Rocío, Fernández, Isabel, Montero-Vallejo, Rocío, Karsdal, Morten, Rasmussen, Daniel Guldager Kring, Leeming, Diana Julie, Sinisi, Antonia, Musa, Kishwar, Sandt, Estelle, Tonini, Manuela, Bugianesi, Elisabetta, Rosso, Chiara, Armandi, Angelo, Marra, Fabio, Gastaldelli, Amalia, Svegliati, Gianluca, Boursier, Jérôme, Francque, Sven, Vonghia, Luisa, Driessen, Ann, Ekstedt, Mattias, Kechagias, Stergios, Yki-Järvinen, Hannele, Porthan, Kimmo, Arola, Johanna, van Mil, Saskia, Papatheodoridis, George, Cortez-Pinto, Helena, Rodrigues, Cecilia M P, Valenti, Luca, Pelusi, Serena, Petta, Salvatore, Pennisi, Grazia, Miele, Luca, Geier, Andreas, Trautwein, Christian, Reißing, Johanna, Aithal, Guruprasad P, Francis, Susan, Palaniyappan, Naaventhan, Bradley, Christopher, Hockings, Paul, Schneider, Moritz, Newsome, Philip, Hübscher, Stefan, Wenn, David, Rosenquist, Christian, Trylesinski, Aldo, Mayo, Rebeca, Alonso, Cristina, Duffin, Kevin, Perfield, James W, Chen, Yu, Yunis, Carla, Tuthill, Theresa, Harrington, Magdalena Alicia, Miller, Melissa, Chen, Yan, McLeod, Euan James, Ross, Trenton, Bernardo, Barbara, Schölch, Corinna, Ertle, Judith, Younes, Ramy, Oldenburger, Anouk, Coxson, Harvey, Ostroff, Rachel, Alexander, Leigh, Biegel, Hannah, Kjær, Mette Skalshøi, Harder, Lea Mørch, Davidsen, Peter, Ellegaard, Jens, Balp, Maria-Magdalena, Brass, Clifford, Jennings, Lori, Martic, Miljen, Löffler, Jürgen, Applegate, Douglas, Shankar, Sudha, Torstenson, Richard, Lindén, Daniel, Fournier-Poizat, Céline, Llorca, Anne, Kalutkiewicz, Michael, Pepin, Kay, Ehman, Richard, Horan, Gerald, Ho, Gideon, Tai, Dean, Chng, Elaine, Patterson, Scott D, Billin, Andrew, Doward, Lynda, Twiss, James, Thakker, Paresh, Derdak, Zoltan, Landgren, Henrik, Lackner, Carolin, Gouw, Annette, Hytiroglou, Prodromos, Mózes, Ferenc E, Lee, Jenny A, Alzoubi, Osama, Staufer, Katharina, Trauner, Michael, Paternostro, Rafael, Stauber, Rudolf E, van Dijk, Anne-Marieke, Mak, Anne Linde, de Saint Loup, Marc, Shima, Toshihide, Gaia, Silvia, Shalimar, Lupșor-Platon, Monica, Wong, Vincent Wai-Sun, Li, Guanlin, Wong, Grace Lai-Hung, Karlas, Thomas, Wiegand, Johannes, Sebastiani, Giada, Tsochatzis, Emmanuel, Liguori, Antonio, Yoneda, Masato, Nakajima, Atsushi, Hagström, Hannes, Akbari, Camilla, Hirooka, Masashi, Chan, Wah-Kheong, Mahadeva, Sanjiv, Rajaram, Ruveena, Zheng, Ming-Hua, George, Jacob, Eslam, Mohammed, Viganò, Mauro, Ridolfo, Sofia, Aithal, Guruprasad Padur, Lee, Dae Ho, Nasr, Patrik, Cassinotto, Christophe, de Lédinghen, Victor, Mendoza, Yuly P, Noureddin, Mazen, Truong, Emily, and Harrison, Stephen A

Published
2023
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35. Impact of Interventional Policies Including Vaccine on COVID-19 Propagation and Socio-economic Factors: Predictive Model Enabling Simulations Using Machine Learning and Big Data

Author

Wu, Haonan, Banerjee, Rajarshi, Venkatachalam, Indhumathi, Chougale, Praveen, 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, and Arai, Kohei, editor

Published
2022
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38. OS-020 MRI-serum based score accurately identifies liver transplant patients without rejection avoiding need for liver biopsy: a multisite european study

Author

Schaapman, Jelte, primary, Shumbayawonda, Elizabeth, additional, Castelo-Branco, Miguel, additional, Alves, Filipe Caseiro, additional, Costa, Tania, additional, Fitzpatrick, Emer, additional, Tupper, Katie, additional, Dhawan, Anil, additional, Deheragoda, Maesha, additional, Sticova, Eva, additional, French, Marika, additional, Beyer, Cayden, additional, Rymell, Soubera, additional, Tonev, Dimitar, additional, Verspaget, Hein W, additional, Neubauer, Stefan, additional, Banerjee, Rajarshi, additional, Lamb, Hildo, additional, and Coenraad, Minneke, additional

Published
2024
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40. WED-238 High pancreatic fat and reduced volume stratify patients with F4 liver fibrosis

Author

Jackson, Edward, primary, Bagur, Alexandre Triay, additional, Beyer, Cayden, additional, Tan, En Ying, additional, Jumat, Nur Halisah Binte, additional, Riddell, Sophie, additional, Shumbayawonda, Elizabeth, additional, Dennis, Andrea, additional, Brears, Helena Thomaides, additional, Banerjee, Rajarshi, additional, Muthiah, Mark, additional, and Dan, Yock Young, additional

Published
2024
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42. WED-268 Natural history and expected change over time for MRI derived cT1: Data from clinical trials and the UK Biobank

Author

Diamond, Charlie, primary, Beyer, Cayden, additional, Shumbayawonda, Elizabeth, additional, McGonigle, John, additional, Rolph, Tim, additional, Yale, Kitty, additional, Banerjee, Rajarshi, additional, Brears, Helena Thomaides, additional, Dennis, Andrea, additional, Pansini, Michele, additional, and Alkhouri, Naim, additional

Published
2024
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45. Directed-Energy Deposition

Author

Nartu, Mohan Sai Kiran Kumar Yadav, primary, Sharma, Shashank, additional, Mantri, Srinivas Aditya, additional, Joshi, Sameehan S., additional, Pantawane, Mangesh V., additional, Mazumder, Sangram, additional, Dahotre, Narendra B., additional, and Banerjee, Rajarshi, additional

Published
2022
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