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Girish N. Nadkarni
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2020 – today
- 2024
- [j15]Wonsuk Oh, Pushkala Jayaraman, Pranai Tandon, Udit S. Chaddha, Patricia H. Kovatch, Alexander W. Charney, Benjamin S. Glicksberg, Girish N. Nadkarni:
A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19. Artif. Intell. Medicine 148: 102750 (2024) - [j14]Benjamin S. Glicksberg, Prem Timsina, Dhaval Patel, Ashwin Sawant, Akhil Vaid, Ganesh Raut, Alexander W. Charney, Donald Apakama, Brendan G. Carr, Robert Freeman, Girish N. Nadkarni, Eyal Klang:
Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room. J. Am. Medical Informatics Assoc. 31(9): 1921-1928 (2024) - [j13]Akhil Vaid, Son Q. Duong, Joshua Lampert, Patricia H. Kovatch, Robert Freeman, Edgar Argulian, Lori Croft, Stamatios Lerakis, Martin Goldman, Rohan Khera, Girish N. Nadkarni:
Local large language models for privacy-preserving accelerated review of historic echocardiogram reports. J. Am. Medical Informatics Assoc. 31(9): 2097-2102 (2024) - [j12]Faris F. Gulamali, Pushkala Jayaraman, Ashwin S. Sawant, Jacob Desman, Benjamin Fox, Annette Chang, Brian Y. Soong, Naveen Arivazagan, Alexandra S. Reynolds, Son Q. Duong, Akhil Vaid, Patricia H. Kovatch, Robert Freeman, Ira Hofer, Ankit Sakhuja, Neha S. Dangayach, David S. Reich, Alexander W. Charney, Girish N. Nadkarni:
Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension. npj Digit. Medicine 7(1) (2024) - [j11]Joy Jiang, Ha My Thi Vy, Alexander Charney, Patricia H. Kovatch, Vivek Reddy, Pushkala Jayaraman, Ron Do, Rohan Khera, Sumeet Chugh, Deepak L. Bhatt, Akhil Vaid, Joshua Lampert, Girish N. Nadkarni:
Multimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population. npj Digit. Medicine 7(1) (2024) - [j10]Lathan Liou, Erick Scott, Prathamesh Parchure, Yuxia Ouyang, Natalia Egorova, Robert Freeman, Ira Hofer, Girish N. Nadkarni, Prem Timsina, Arash Kia, Matthew A. Levin:
Assessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system. npj Digit. Medicine 7(1) (2024) - [i6]Akhil Vaid, Joshua Lampert, Juhee Lee, Ashwin Sawant, Donald Apakama, Ankit Sakhuja, Ali Soroush, Denise Lee, Isotta Landi, Nicole Bussola, Ismail Nabeel, Robbie Freeman, Patricia H. Kovatch, Brendan G. Carr, Benjamin S. Glicksberg, Edgar Argulian, Stamatios Lerakis, Monica Kraft, Alexander Charney, Girish N. Nadkarni:
Generative Large Language Models are autonomous practitioners of evidence-based medicine. CoRR abs/2401.02851 (2024) - [i5]Braja Gopal Patra, Lauren A. Lepow, Praneet Kasi Reddy Jagadeesh Kumar, Veer Vekaria, Mohit Manoj Sharma, Prakash Adekkanattu, Brian Fennessy, Gavin Hynes, Isotta Landi, Jorge A. Sanchez-Ruiz, Euijung Ryu, Joanna M. Biernacka, Girish N. Nadkarni, Ardesheer Talati, Myrna Weissman, Mark Olfson, J. John Mann, Alexander W. Charney, Jyotishman Pathak:
Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model. CoRR abs/2403.17199 (2024) - 2023
- [j9]Akhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua Lampert, Alexander Charney, Hayit Greenspan, Jagat Narula, Benjamin S. Glicksberg, Girish N. Nadkarni:
A foundational vision transformer improves diagnostic performance for electrocardiograms. npj Digit. Medicine 6 (2023) - [c7]Faris F. Gulamali, Ashwin Sawant, Ira Hofer, Matthew A. Levin, Alexander Charney, Karandeep Singh, Benjamin S. Glicksberg, Girish N. Nadkarni:
Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn). MLHC 2023: 230-247 - [i4]Faris F. Gulamali, Ashwin S. Sawant, Lora Liharska, Carol R. Horowitz, Lili Chan, Patricia H. Kovatch, Ira Hofer, Karandeep Singh, Lynne D. Richardson, Emmanuel Mensah, Alexander W. Charney, David L. Reich, Jianying Hu, Girish N. Nadkarni:
An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasets. CoRR abs/2311.03425 (2023) - 2022
- [j8]Jie Cao, Xiaosong Zhang, Vahakn Shahinian, Huiying Yin, Diane Steffick, Rajiv Saran, Susan Crowley, Michael Mathis, Girish N. Nadkarni, Michael Heung, Karandeep Singh:
Generalizability of an acute kidney injury prediction model across health systems. Nat. Mac. Intell. 4(12): 1121-1129 (2022) - [j7]Faris F. Gulamali, Ashwin Sawant, Patricia H. Kovatch, Benjamin S. Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric K. Oermann:
Autoencoders for sample size estimation for fully connected neural network classifiers. npj Digit. Medicine 5 (2022) - [i3]Akhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua Lampert, Alexander Charney, Hayit Greenspan, Benjamin S. Glicksberg, Jagat Narula, Girish N. Nadkarni:
HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes. CoRR abs/2212.14040 (2022) - 2021
- [j6]Jessica K. De Freitas, Kipp W. Johnson, Eddye Golden, Girish N. Nadkarni, Joel T. Dudley, Erwin P. Bottinger, Benjamin S. Glicksberg, Riccardo Miotto:
Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records. Patterns 2(9): 100337 (2021) - [j5]Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Jing Zhang, Riccardo Miotto, Zhangyang Wang, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg:
Contrastive learning improves critical event prediction in COVID-19 patients. Patterns 2(12): 100389 (2021) - [j4]Tingyi Wanyan, Akhil Vaid, Jessica K. De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N. Nadkarni, Ariful Azad, Ying Ding, Benjamin S. Glicksberg:
Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit. IEEE Trans. Big Data 7(1): 38-44 (2021) - [c6]Lauren A. Lepow, Braja Gopal Patra, Isotta Landi, Prakash Adekkanattu, Jyotishman Pathak, Mark Olfson, J. John Mann, Euijung Ryu, Joanna M. Biernacka, Girish N. Nadkarni, Priya Wickramaratne, Myrna Weissman, Benjamin S. Glicksberg, Alexander Charney:
Extracting Social Isolation Information From Psychiatric Notes in the Electronic Health Records. AMIA 2021 - [i2]Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Riccardo Miotto, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg:
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients. CoRR abs/2101.04013 (2021) - 2020
- [j3]Fayzan F. Chaudhry, Matteo Danieletto, Eddye Golden, Jerome R. Scelza, Greg Botwin, Mark M. Shervey, Jessica K. De Freitas, Ishan Paranjpe, Girish N. Nadkarni, Riccardo Miotto, Patricia Glowe, Greg Stock, Bethany Percha, Noah Zimmerman, Joel T. Dudley, Benjamin S. Glicksberg:
Sleep in the Natural Environment: A Pilot Study. Sensors 20(5): 1378 (2020) - [c5]Tingyi Wanyan, Martin Kang, Marcus A. Badgeley, Kipp W. Johnson, Jessica K. De Freitas, Fayzan F. Chaudhry, Akhil Vaid, Shan Zhao, Riccardo Miotto, Girish N. Nadkarni, Fei Wang, Justin F. Rousseau, Ariful Azad, Ying Ding, Benjamin S. Glicksberg:
Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions. AIME 2020: 14-25 - [i1]Stefan Konigorski, Sarah Wernicke, Tamara Slosarek, Alexander M. Zenner, Nils Strelow, Ferenc D. Ruether, Florian Henschel, Manisha Manaswini, Fabian Pottbäcker, Jonathan A. Edelman, Babajide Alamu Owoyele, Matteo Danieletto, Eddye Golden, Micol Zweig, Girish N. Nadkarni, Erwin P. Böttinger:
StudyU: a platform for designing and conducting innovative digital N-of-1 trials. CoRR abs/2012.14201 (2020)
2010 – 2019
- 2019
- [j2]Tielman T. Van Vleck, Lili Chan, Steven G. Coca, Catherine K. Craven, Ron Do, Stephen B. Ellis, Joseph L. Kannry, Ruth J. F. Loos, Peter A. Bonis, Judy Cho, Girish N. Nadkarni:
Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression. Int. J. Medical Informatics 129: 334-341 (2019) - 2015
- [j1]Anima Singh, Girish N. Nadkarni, Omri Gottesman, Stephen B. Ellis, Erwin P. Bottinger, John V. Guttag:
Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration. J. Biomed. Informatics 53: 220-228 (2015) - [c4]Yoonjung Y. Joo, Jennifer A. Pacheco, Loren L. Armstrong, William K. Thompson, Robert J. Carroll, Joshua C. Denny, Peggy L. Peissig, James G. Linneman, Jyotishman Pathak, Girish N. Nadkarni, Laura Rasmussen-Torvik, M. Geoffrey Hayes, Abel N. Kho:
A Genome- and Phenome- Wide Study of Diverticulosis. AMIA 2015 - 2014
- [c3]Ilkka Huopaniemi, Girish N. Nadkarni, Rajiv Nadukuru, Vaneet Lotay, Stephen B. Ellis, Omri Gottesman, Erwin P. Bottinger:
Disease progression subtype discovery from longitudinal EMR data with a majority of missing values and unknown initial time points. AMIA 2014 - [c2]Girish N. Nadkarni, Omri Gottesman, James G. Linneman, Herbert S. Chase, Richard L. Berg, Samira Farouk, Vaneet Lotay, Stephen B. Ellis, George Hripcsak, Peggy L. Peissig, Chunhua Weng, Rajiv Nadukuru, Erwin P. Bottinger:
Development and validation of an electronic phenotyping algorithm for chronic kidney disease. AMIA 2014 - [c1]Anima Singh, Girish N. Nadkarni, John V. Guttag, Erwin P. Bottinger:
Leveraging hierarchy in medical codes for predictive modeling. BCB 2014: 96-103
Coauthor Index
aka: Alexander W. Charney
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last updated on 2024-09-18 01:09 CEST by the dblp team
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