Amol A. Verma

According to our database, Amol A. Verma authored at least 12 papers between 2020 and 2025.

Collaborative distances:

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

2025

Reliably detecting model failures in deployment without labels.

Viet Nguyen, Changjian Shui, Vijay Giri, Siddarth Arya, Amol Verma, Fahad Razak, Rahul G. Krishnan

CoRR, June, 2025

Optimizing the efficiency and effectiveness of data quality assurance in a multicenter clinical dataset.

Anne Fu, Trong Shen, Surain B. Roberts, Weihan Liu, Shruthi Vaidyanathan, Kayley-Jasmin Marchena-Romero, Yuen Yu Phyllis Lam, Kieran Shah, Denise Y. F. Mak, Stephen Chin, Seth J. Stern, Radha Koppula, Lisa F. Joyce, Nicholas Pellegrino, Nancy Harris, Vivian Ng, Siddhartha Srivastava, Nathaniel Manikan, Amelia Wilkinson, Jenny Gastmeier, Jason C. Kwan, Hapiloe Byaruhanga, Linia Shaji, Siji George, Stephanie Handsor, Reshma Anna Roy, Chong Sung Kim, Selam Mequanint, Fahad Razak, Amol A. Verma

J. Am. Medical Informatics Assoc., 2025

Approaches to identify scenarios for data science implementations within healthcare settings: recommendations based on experiences at multiple academic institutions.

Lillian Sung, Michael Brudno, Michael C. W. Caesar, Amol A. Verma, Brad Buchsbaum, Ravi Retnakaran, Vasily Giannakeas, Azadeh Kushki, Gary D. Bader, Helen Lasthiotakis, Muhammad Mamdani, Lisa Strug

Frontiers Digit. Health, 2025

2024

Development and external validation of tools for categorizing diagnosis codes in international hospital data.

Sarah L. Malecki, Anne Loffler, Daniel Tamming, Niklas Dyrby Johansen, Tor Biering-Sørensen, Michael Fralick, Shahmir Sohail, Jessica Shi, Surain B. Roberts, Michael Colacci, Marwa Ismail, Fahad Razak, Amol A. Verma

Int. J. Medical Informatics, 2024

Decentralised, Collaborative, and Privacy-preserving Machine Learning for Multi-Hospital Data.

Congyu Fang, Adam Dziedzic, Lin Zhang, Laura Oliva, Amol Verma, Fahad Razak, Nicolas Papernot, Bo Wang

CoRR, 2024

A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets.

Fatemeh Tavakoli, David B. Emerson, Sana Ayromlou, John Taylor Jewell, Amrit Krishnan, Yuchong Zhang, Amol Verma, Fahad Razak

Proceedings of the Machine Learning for Healthcare Conference, 2024

2023

FENDA-FL: Personalized Federated Learning on Heterogeneous Clinical Datasets.

Fatemeh Tavakoli, David B. Emerson, John Jewell, Amrit Krishnan, Yuchong Zhang, Amol Verma, Fahad Razak

CoRR, 2023

Assessing the impact of emergency department short stay units using length-of-stay prediction and discrete event simulation.

Mucahit Cevik, Can Kavaklioglu, Fahad Razak, Amol Verma, Ayse Basar

CoRR, 2023

2022

From compute to care: Lessons learned from deploying an early warning system into clinical practice.

Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, Muhammad Mamdani, Amol A. Verma

Frontiers Digit. Health, 2022

2021

Assessing the quality of clinical and administrative data extracted from hospitals: the General Medicine Inpatient Initiative (GEMINI) experience.

Amol A. Verma, Sachin V. Pasricha, Hae Young Jung, Vladyslav Kushnir, Denise Y. F. Mak, Radha Koppula, Yishan Guo, Janice L. Kwan, Lauren Lapointe-Shaw, Shail Rawal, Terence Tang, Adina Weinerman, Fahad Razak

J. Am. Medical Informatics Assoc., 2021

2020

Accuracy of the Preferred Language Field in the Electronic Health Records of Two Canadian Hospitals.

Akshay Rajaram, Daniel Thomas, Faten Sallam, Amol A. Verma, Shail Rawal

Appl. Clin. Inform., 2020

Preparing a Clinical Support Model for Silent Mode in General Internal Medicine.

Bret Nestor, Liam G. McCoy, Amol Verma, Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi

Proceedings of the Machine Learning for Healthcare Conference, 2020