activity
20202026
most citedFederated Learning for Healthcare Domain - Pipeline, Applications and Challenges

199 citations · 412 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Xucheng Wang, Xiaoman Zhang, Sung Eun Kim +2

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-language models (VLMs) could enable autonomous ultrasound systems, but existing benchma…

cs.CV2025

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…

cs.CL2024★ 11 cited

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…

cs.CL2023

CLIFT: Analysing Natural Distribution Shift on Question Answering Models in Clinical Domain

Ankit Pal

This paper introduces a new testbed CLIFT (Clinical Shift) for the clinical domain Question-answering task. The testbed includes 7.5k high-quality question answering samples to pro…

cs.CL2023★ 18 cited

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…

cs.LG2022★ 199 cited

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…

cs.CL2022

DeepParliament: A Legal domain Benchmark & Dataset for Parliament Bills Prediction

Ankit Pal

This paper introduces DeepParliament, a legal domain Benchmark Dataset that gathers bill documents and metadata and performs various bill status classification tasks. The proposed…

cs.CL2022★ 74 cited

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…

cs.LG2020★ 13 cited

Pay Attention to the cough: Early Diagnosis of COVID-19 using Interpretable Symptoms Embeddings with Cough Sound Signal Processing

Ankit Pal, Malaikannan Sankarasubbu

COVID-19 (coronavirus disease 2019) pandemic caused by SARS-CoV-2 has led to a treacherous and devastating catastrophe for humanity. At the time of writing, no specific antivirus d…

cs.CL2020★ 97 cited

Multi-Label Text Classification using Attention-based Graph Neural Network

Ankit Pal, Muru Selvakumar, Malaikannan Sankarasubbu

In Multi-Label Text Classification (MLTC), one sample can belong to more than one class. It is observed that most MLTC tasks, there are dependencies or correlations among labels. E…