199 citations · 296 across the 6 of their papers we have counts for
13 papers
ReXVQA: A Large-scale Visual Question Answering Benchmark for Generalist Chest X-ray Understanding
Ankit Pal, Jung-Oh Lee, Xiaoman Zhang +5
We present ReXVQA, the largest and most comprehensive benchmark for visual question answering (VQA) in chest radiology, comprising approximately 696,000 questions paired with 160,0…
Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & Hallucinations
Ankit Pal, Malaikannan Sankarasubbu
Large language models have the potential to be valuable in the healthcare industry, but it's crucial to verify their safety and effectiveness through rigorous evaluation. For this…
Med-HALT: Medical Domain Hallucination Test for Large Language Models
Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu
This research paper focuses on the challenges posed by hallucinations in large language models (LLMs), particularly in the context of the medical domain. Hallucination, wherein the…
Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges
Madhura Joshi, Ankit Pal, Malaikannan Sankarasubbu
Federated learning is the process of developing machine learning models over datasets distributed across data centers such as hospitals, clinical research labs, and mobile devices…
MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering
Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu
This paper introduces MedMCQA, a new large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. More than 194k h…
Bayesian Optimization of Bose-Einstein Condensates
Tamil Arasan Bakthavatchalam, Suriyadeepan Ramamoorthy, Malaikannan Sankarasubbu +2
Machine Learning methods are emerging as faster and efficient alternatives to numerical simulation techniques. The field of Scientific Computing has started adopting these data-dri…