Zobrazeno 1 - 10
of 690
pro vyhledávání: '"N. Nadkarni"'
Autor:
Dhavalkumar Patel, Ganesh Raut, Eyal Zimlichman, Satya Narayan Cheetirala, Girish N Nadkarni, Benjamin S. Glicksberg, Donald U. Apakama, Elijah J. Bell, Robert Freeman, Prem Timsina, Eyal Klang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract This study was designed to assess how different prompt engineering techniques, specifically direct prompts, Chain of Thought (CoT), and a modified CoT approach, influence the ability of GPT-3.5 to answer clinical and calculation-based medica
Externí odkaz:
https://doaj.org/article/0ec337c7b65e4235a13500d8ea050f4a
Autor:
Miguel Rodriguez de los Santos, Brian H. Kopell, Ariela Buxbaum Grice, Gauri Ganesh, Andy Yang, Pardis Amini, Lora E. Liharska, Eric Vornholt, John F. Fullard, Pengfei Dong, Eric Park, Sarah Zipkowitz, Deepak A. Kaji, Ryan C. Thompson, Donjing Liu, You Jeong Park, Esther Cheng, Kimia Ziafat, Emily Moya, Brian Fennessy, Lillian Wilkins, Hannah Silk, Lisa M. Linares, Brendan Sullivan, Vanessa Cohen, Prashant Kota, Claudia Feng, Jessica S. Johnson, Marysia-Kolbe Rieder, Joseph Scarpa, Girish N. Nadkarni, Minghui Wang, Bin Zhang, Pamela Sklar, Noam D. Beckmann, Eric E. Schadt, Panos Roussos, Alexander W. Charney, Michael S. Breen
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. W
Externí odkaz:
https://doaj.org/article/da9c46017e36443fb5aa615c25a1975d
Autor:
Lathan Liou, Erick Scott, Prathamesh Parchure, Yuxia Ouyang, Natalia Egorova, Robert Freeman, Ira S. Hofer, Girish N. Nadkarni, Prem Timsina, Arash Kia, Matthew A. Levin
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-7 (2024)
Abstract Malnutrition is a frequently underdiagnosed condition leading to increased morbidity, mortality, and healthcare costs. The Mount Sinai Health System (MSHS) deployed a machine learning model (MUST-Plus) to detect malnutrition upon hospital ad
Externí odkaz:
https://doaj.org/article/5aac2935948f402294eaf43cbf6878bf
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Chronic kidney disease (CKD) is a complex disorder that causes a gradual loss of kidney function, affecting approximately 9.1% of the world's population. Here, we use a soft-clustering algorithm to deconstruct its genetic heterogeneity. Firs
Externí odkaz:
https://doaj.org/article/b75974ffa9ce437ca33061c4fc0d8d06
Autor:
Mahmud Omar, Shelly Soffer, Alexander W. Charney, Isotta Landi, Girish N. Nadkarni, Eyal Klang
Publikováno v:
Frontiers in Psychiatry, Vol 15 (2024)
BackgroundWith their unmatched ability to interpret and engage with human language and context, large language models (LLMs) hint at the potential to bridge AI and human cognitive processes. This review explores the current application of LLMs, such
Externí odkaz:
https://doaj.org/article/d9e1dd773a334da983bfae6ba1f3cfd4
Publikováno v:
BMC Nephrology, Vol 24, Iss 1, Pp 1-10 (2023)
Abstract Introduction End-stage kidney disease (ESKD) is associated with increased morbidity and mortality. Identifying patients with stage 4 CKD (CKD4) at risk of rapid progression to ESKD remains challenging. Accurate prediction of CKD4 progression
Externí odkaz:
https://doaj.org/article/613859e75f8e47d1a6cf0b6e15c307ca
Autor:
Miguel Rodriguez de los Santos, Brian H. Kopell, Ariela Buxbaum Grice, Gauri Ganesh, Andy Yang, Pardis Amini, Lora E. Liharska, Eric Vornholt, John F. Fullard, Pengfei Dong, Eric Park, Sarah Zipkowitz, Deepak A. Kaji, Ryan C. Thompson, Donjing Liu, You Jeong Park, Esther Cheng, Kimia Ziafat, Emily Moya, Brian Fennessy, Lillian Wilkins, Hannah Silk, Lisa M. Linares, Brendan Sullivan, Vanessa Cohen, Prashant Kota, Claudia Feng, Jessica S. Johnson, Marysia-Kolbe Rieder, Joseph Scarpa, Girish N. Nadkarni, Minghui Wang, Bin Zhang, Pamela Sklar, Noam D. Beckmann, Eric E. Schadt, Panos Roussos, Alexander W. Charney, Michael S. Breen
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/6b78479b7e5842348e4a57387c084ff0
Autor:
Kullaya Takkavatakarn, Yang Dai, Huei Hsun Wen, Justin Kauffman, Alexander Charney, Steven G Coca, Girish N Nadkarni, Lili Chan
Publikováno v:
PLoS ONE, Vol 19, Iss 2, p e0297919 (2024)
BackgroundArea-level social determinants of health (SDOH) based on patients' ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could be used to derive individua
Externí odkaz:
https://doaj.org/article/e19e210c88f04c06b55d4283ab7503a4
Autor:
Joji Tokita, David Lam, Aida Vega, Stephanie Wang, Leonard Amoruso, Tamara Muller, Nidhi Naik, Shivani Rathi, Sharlene Martin, Azadeh Zabetian, Catherine Liu, Catherine Sinfield, Tony McNicholas, Fergus Fleming, Steven G. Coca, Girish N Nadkarni, Roger Tun, Mike Kattan, Michael J. Donovan, Arshad K. Rahim
Publikováno v:
Journal of Primary Care & Community Health, Vol 15 (2024)
Introduction/Objective: The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient’s risk for a progressive decline in kidney function over 5
Externí odkaz:
https://doaj.org/article/096b358f11364f89bec96d7956413255
Autor:
Son Q. Duong, Akhil Vaid, Vy Thi Ha My, Liam R. Butler, Joshua Lampert, Robert H. Pass, Alexander W. Charney, Jagat Narula, Rohan Khera, Ankit Sakhuja, Hayit Greenspan, Bruce D. Gelb, Ron Do, Girish N. Nadkarni
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 13, Iss 1 (2024)
Background Right ventricular ejection fraction (RVEF) and end‐diastolic volume (RVEDV) are not readily assessed through traditional modalities. Deep learning–enabled ECG analysis for estimation of right ventricular (RV) size or function is unexpl
Externí odkaz:
https://doaj.org/article/5493fdcd7dd54c148a3db367814dc8e4