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ORCIDGirish N. Nadkarni
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2020 – today
- 2025
[j22]Mahmud Omar
, Saleh Nassar, Kareem Hijazi, Benjamin S. Glicksberg, Girish N. Nadkarni, Eyal Klang:
Generating credible referenced medical research: A comparative study of openAI's GPT-4 and Google's gemini. Comput. Biol. Medicine 185: 109545 (2025)- [j21]Mahmud Omar, Benjamin S. Glicksberg, Girish N. Nadkarni, Eyal Klang:
Refining LLMs outputs with iterative consensus ensemble (ICE). Comput. Biol. Medicine 196: 110731 (2025) - [j20]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, Yiye Zhang, Alexander W. Charney, Jyotishman Pathak:
Extracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model. J. Am. Medical Informatics Assoc. 32(1): 218-226 (2025) - [j19]Jacob Desman, Zhang-Wei Hong, Moein Sabounchi, Ashwin S. Sawant, Jaskirat Gill, Ana C. Costa, Gagan Kumar, Rajeev Sharma, Arpeta Gupta, Paul McCarthy, Veena Nandwani, Doug Powell, Alexandra Carideo, Donnie Goodwin, Sanam Ahmed, Umesh Gidwani, Matthew A. Levin, Robin Varghese, Farzan Filsoufi, Robert Freeman, Avniel Shetreat-Klein, Alexander W. Charney, Ira S. Hofer, Lili Chan, David Reich, Patricia H. Kovatch, Roopa Kohli-Seth, Monica Kraft, Pulkit Agrawal, John A. Kellum, Girish N. Nadkarni, Ankit Sakhuja:
A distributional reinforcement learning model for optimal glucose control after cardiac surgery. npj Digit. Medicine 8(1) (2025) - [j18]Shelly Soffer, Vera Sorin, Girish N. Nadkarni, Eyal Klang:
Pitfalls of large language models in medical ethics reasoning. npj Digit. Medicine 8(1) (2025) - [i12]Nariman Naderi, Seyed Amir Ahmad Safavi-Naini, Thomas Savage, Zahra Atf, Peter Lewis, Girish N. Nadkarni, Ali Soroush:
Self-Reported Confidence of Large Language Models in Gastroenterology: Analysis of Commercial, Open-Source, and Quantized Models. CoRR abs/2503.18562 (2025) - [i11]Mohammad Amin Khalafi, Seyed Amir Ahmad Safavi-Naini, Ameneh Salehi, Nariman Naderi, Dorsa Alijanzadeh, Pardis Ketabi Moghadam, Kaveh Kavosi, Negar Golestani, Shabnam Shahrokh, Soltanali Fallah, Jamil S. Samaan, Nicholas P. Tatonetti, Nicholas Hoerter, Girish N. Nadkarni, Hamid Asadzadeh Aghdaei, Ali Soroush:
Vision Language Models versus Machine Learning Models Performance on Polyp Detection and Classification in Colonoscopy Images. CoRR abs/2503.21840 (2025) - [i10]Satya Narayan Cheetirala, Ganesh Raut, Dhavalkumar Patel, Fabio Sanatana, Robert Freeman, Matthew A. Levin, Girish N. Nadkarni, Omar Dawkins, Reba Miller, Randolph M. Steinhagen, Eyal Klang, Prem Timsina:
Less Context, Same Performance: A RAG Framework for Resource-Efficient LLM-Based Clinical NLP. CoRR abs/2505.20320 (2025) - 2024
- [j17]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) - [j16]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) - [j15]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) - [j14]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 S. 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) - [j13]Pushkala Jayaraman, Jacob Desman, Moein Sabounchi, Girish N. Nadkarni, Ankit Sakhuja:
A Primer on Reinforcement Learning in Medicine for Clinicians. npj Digit. Medicine 7(1) (2024) - [j12]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) - [j11]Eyal Klang, Donald Apakama, Ethan E. Abbott, Akhil Vaid, Joshua Lampert, Ankit Sakhuja, Robert Freeman, Alexander W. Charney, David Reich, Monica Kraft, Girish N. Nadkarni, Benjamin S. Glicksberg:
A strategy for cost-effective large language model use at health system-scale. npj Digit. Medicine 7(1) (2024) - [j10]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:
Assessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system. npj Digit. Medicine 7(1) (2024) - [i9]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) - [i8]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) - [i7]Seyed Amir Ahmad Safavi-Naini, Shuhaib Ali, Omer Shahab, Zahra Shahhoseini, Thomas Savage, Sara Rafiee, Jamil S. Samaan, Reem Al Shabeeb, Farah Ladak, Jamie O. Yang, Juan Echavarria, Sumbal Babar, Aasma Shaukat, Samuel Margolis, Nicholas P. Tatonetti, Girish N. Nadkarni, Bara El Kurdi, Ali Soroush:
Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models. CoRR abs/2409.00084 (2024) - [i6]Mohammadreza Ghaffarzadeh-Esfahani, Mahdi Ghaffarzadeh-Esfahani, Arian Salahi-Niri, Hossein Toreyhi, Zahra Atf, Amirali Mohsenzadeh-Kermani, Mahshad Sarikhani, Zohreh Tajabadi, Fatemeh Shojaeian, Mohammad Hassan Bagheri, Aydin Feyzi, Mohammadamin Tarighatpayma, Narges Gazmeh, Fateme Heydari, Hossein Afshar, Amirreza Allahgholipour, Farid Alimardani, Ameneh Salehi, Naghmeh Asadimanesh, Mohammad Amin Khalafi, Hadis Shabanipour, Ali Moradi, Sajjad Hossein Zadeh, Omid Yazdani, Romina Esbati, Moozhan Maleki, Danial Samiei Nasr, Amirali Soheili, Hossein Majlesi, Saba Shahsavan, Alireza Soheilipour, Nooshin Goudarzi, Erfan Taherifard, Hamidreza Hatamabadi, Jamil S. Samaan, Thomas Savage, Ankit Sakhuja, Ali Soroush, Girish N. Nadkarni, Ilad Alavi Darazam, Mohamad Amin Pourhoseingholi, Seyed Amir Ahmad Safavi-Naini:
Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data. CoRR abs/2409.02136 (2024) - [i5]Dhavalkumar Patel, Ganesh Raut, Satya Narayan Cheetirala, Girish N. Nadkarni, Robert Freeman, Benjamin S. Glicksberg, Eyal Klang, Prem Timsina:
Cloud Platforms for Developing Generative AI Solutions: A Scoping Review of Tools and Services. CoRR abs/2412.06044 (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 S. 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 S. 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
Alexander Charney
aka: Alexander W. Charney
aka: Alexander W. Charney
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