Akhil Vaid

According to our database, Akhil Vaid authored at least 12 papers between 2020 and 2024.

Collaborative distances:

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

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

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

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

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

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

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

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