Girish N. Nadkarni

According to our database, Girish N. Nadkarni authored at least 34 papers between 2014 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Extracting social support and social isolation information from clinical psychiatry notes: comparing a rule-based natural language processing system and a large language model.

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

J. Am. Medical Informatics Assoc., 2025

2024

Assessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system.

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

npj Digit. Medicine, 2024

A strategy for cost-effective large language model use at health system-scale.

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

npj Digit. Medicine, 2024

Multimodal fusion learning for long QT syndrome pathogenic genotypes in a racially diverse population.

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

npj Digit. Medicine, 2024

A Primer on Reinforcement Learning in Medicine for Clinicians.

Pushkala Jayaraman, Jacob Desman, Moein Sabounchi, Girish N. Nadkarni, Ankit Sakhuja

npj Digit. Medicine, 2024

Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension.

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

npj Digit. Medicine, 2024

Local large language models for privacy-preserving accelerated review of historic echocardiogram reports.

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

J. Am. Medical Informatics Assoc., 2024

Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room.

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

J. Am. Medical Informatics Assoc., 2024

Cloud Platforms for Developing Generative AI Solutions: A Scoping Review of Tools and Services.

Dhavalkumar Patel, Ganesh Raut, Satya Narayan Cheetirala, Girish N. Nadkarni, Robert Freeman, Benjamin S. Glicksberg, Eyal Klang, Prem Timsina

CoRR, 2024

Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data.

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

CoRR, 2024

Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models.

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

CoRR, 2024

Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model.

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

CoRR, 2024

Generative Large Language Models are autonomous practitioners of evidence-based medicine.

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

CoRR, 2024

A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19.

Wonsuk Oh, Pushkala Jayaraman, Pranai Tandon, Udit S. Chaddha, Patricia H. Kovatch, Alexander W. Charney, Benjamin S. Glicksberg, Girish N. Nadkarni

Artif. Intell. Medicine, 2024

2023

A foundational vision transformer improves diagnostic performance for electrocardiograms.

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

npj Digit. Medicine, 2023

An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasets.

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

CoRR, 2023

Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn).

Faris F. Gulamali, Ashwin Sawant, Ira S. Hofer, Matthew A. Levin, Alexander Charney, Karandeep Singh, Benjamin S. Glicksberg, Girish N. Nadkarni

Proceedings of the Machine Learning for Healthcare Conference, 2023

2022

Generalizability of an acute kidney injury prediction model across health systems.

Jie Cao, Xiaosong Zhang, Vahakn Shahinian, Huiying Yin, Diane Steffick, Rajiv Saran, Susan Crowley, Michael Mathis, Girish N. Nadkarni, Michael Heung, Karandeep Singh

Nat. Mac. Intell., December, 2022

Autoencoders for sample size estimation for fully connected neural network classifiers.

Faris F. Gulamali, Ashwin Sawant, Patricia H. Kovatch, Benjamin S. Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric K. Oermann

npj Digit. Medicine, 2022

HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes.

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

CoRR, 2022

2021

Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit.

Tingyi Wanyan, Akhil Vaid, Jessica K. De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N. Nadkarni, Ariful Azad, Ying Ding, Benjamin S. Glicksberg

IEEE Trans. Big Data, 2021

Contrastive learning improves critical event prediction in COVID-19 patients.

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

Patterns, 2021

Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records.

Jessica K. De Freitas, Kipp W. Johnson, Eddye Golden, Girish N. Nadkarni, Joel T. Dudley, Erwin P. Bottinger, Benjamin S. Glicksberg, Riccardo Miotto

Patterns, 2021

Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients.

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

CoRR, 2021

Extracting Social Isolation Information From Psychiatric Notes in the Electronic Health Records.

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

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

Sleep in the Natural Environment: A Pilot Study.

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

Sensors, 2020

StudyU: a platform for designing and conducting innovative digital N-of-1 trials.

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

CoRR, 2020

Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions.

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

Proceedings of the Artificial Intelligence in Medicine, 2020

2019

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.

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

Int. J. Medical Informatics, 2019

2015

Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration.

Anima Singh, Girish N. Nadkarni, Omri Gottesman, Stephen B. Ellis, Erwin P. Bottinger, John V. Guttag

J. Biomed. Informatics, 2015

A Genome- and Phenome- Wide Study of Diverticulosis.

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

Proceedings of the AMIA 2015, 2015

2014

Leveraging hierarchy in medical codes for predictive modeling.

Anima Singh, Girish N. Nadkarni, John V. Guttag, Erwin P. Bottinger

Proceedings of the 5th ACM Conference on Bioinformatics, 2014

Development and validation of an electronic phenotyping algorithm for chronic kidney disease.

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

Proceedings of the AMIA 2014, 2014

Disease progression subtype discovery from longitudinal EMR data with a majority of missing values and unknown initial time points.

Ilkka Huopaniemi, Girish N. Nadkarni, Rajiv Nadukuru, Vaneet Lotay, Stephen B. Ellis, Omri Gottesman, Erwin P. Bottinger

Proceedings of the AMIA 2014, 2014