Zobrazeno 1 - 10
of 410
pro vyhledávání: '"Girish N. Nadkarni"'
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
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
Autor:
Josh Schilling, Sepideh Shokouhi, Aisha Montgomery, Girish N. Nadkarni, Alexander W. Charney, Anil Shanker, Rajbir Singh, Kenar Jhaveri, Karandeep S. Singh, Prashant Khadke, Praduman Jain
Publikováno v:
Communications Medicine, Vol 3, Iss 1, Pp 1-12 (2023)
Abstract Background Decentralized, digital health studies can provide real-world evidence of the lasting effects of COVID-19 on physical, socioeconomic, psychological, and social determinant factors of health in India. Existing research cohorts, howe
Externí odkaz:
https://doaj.org/article/c032adca7d0146508bfa77dd105e32cf
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 (2024)
Externí odkaz:
https://doaj.org/article/8e7d242e3f4e4c2f95575f22fc201267
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
Publikováno v:
Therapeutic Advances in Gastroenterology, Vol 16 (2023)
Background: The integration of artificial intelligence (AI) into healthcare has opened new avenues for enhancing patient care and clinical research. In gastroenterology, the potential of AI tools, specifically large language models like ChatGPT, is b
Externí odkaz:
https://doaj.org/article/589d69a1dd384a2ca72029da88cc376c
Autor:
Ishan Paranjpe, Pushkala Jayaraman, Chen-Yang Su, Sirui Zhou, Steven Chen, Ryan Thompson, Diane Marie Del Valle, Ephraim Kenigsberg, Shan Zhao, Suraj Jaladanki, Kumardeep Chaudhary, Steven Ascolillo, Akhil Vaid, Edgar Gonzalez-Kozlova, Justin Kauffman, Arvind Kumar, Manish Paranjpe, Ross O. Hagan, Samir Kamat, Faris F. Gulamali, Hui Xie, Joceyln Harris, Manishkumar Patel, Kimberly Argueta, Craig Batchelor, Kai Nie, Sergio Dellepiane, Leisha Scott, Matthew A. Levin, John Cijiang He, Mayte Suarez-Farinas, Steven G. Coca, Lili Chan, Evren U. Azeloglu, Eric Schadt, Noam Beckmann, Sacha Gnjatic, Miram Merad, Seunghee Kim-Schulze, Brent Richards, Benjamin S. Glicksberg, Alexander W. Charney, Girish N. Nadkarni
Publikováno v:
Communications Medicine, Vol 3, Iss 1, Pp 1-10 (2023)
Abstract Background Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover
Externí odkaz:
https://doaj.org/article/a59378e85e3b46de854114917b9da8cd
Autor:
Iain S. Forrest, Ben O. Petrazzini, Áine Duffy, Joshua K. Park, Anya J. O’Neal, Daniel M. Jordan, Ghislain Rocheleau, Girish N. Nadkarni, Judy H. Cho, Ashira D. Blazer, Ron Do
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-12 (2023)
Abstract Systemic autoimmune rheumatic diseases (SARDs) can lead to irreversible damage if left untreated, yet these patients often endure long diagnostic journeys before being diagnosed and treated. Machine learning may help overcome the challenges
Externí odkaz:
https://doaj.org/article/b64a1436928b48f396ea73f3b6b5a0c3
Autor:
Akhil Vaid, Edgar Argulian, Stamatios Lerakis, Brett K. Beaulieu-Jones, Chayakrit Krittanawong, Eyal Klang, Joshua Lampert, Vivek Y. Reddy, Jagat Narula, Girish N. Nadkarni, Benjamin S. Glicksberg
Publikováno v:
Communications Medicine, Vol 3, Iss 1, Pp 1-12 (2023)
Vaid et al performed a multi-center retrospective cohort study using electrocardiograms from patients with mitral regurgitation to train a deep learning model to detect valvular disease and validated it in externally. They demonstrate the model could
Externí odkaz:
https://doaj.org/article/00e8d1d949bb475cab324fb51110a6c9