activity
20242026
most citedEntry-level guide to the use of large language models for medical research

2 citations · 2 across the 1 of their papers we have counts for

collaborators

7 papers

cs.AI20262 cited

Entry-level guide to the use of large language models for medical research

Qiao Jin, Nicholas Wan, Robert Leaman +20

Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools capable of revolutionizing variou…

cs.AI2026

A Unified Multimodal Framework for Dataset Construction and Model-Based Diagnosis of Ameloblastoma

Ajo Babu George, Anna Mariam John, Athul Anoop +1

Artificial intelligence (AI)-enabled diagnostics in maxillofacial pathology require structured, high-quality multimodal datasets. However, existing resources provide limited amelob…

cs.AI2025

Evaluation of Causal Reasoning for Large Language Models in Contextualized Clinical Scenarios of Laboratory Test Interpretation

Balu Bhasuran, Mattia Prosperi, Karim Hanna +3

This study evaluates causal reasoning in large language models (LLMs) using 99 clinically grounded laboratory test scenarios aligned with Pearl's Ladder of Causation: association,…

q-bio.MN2025

AI-Driven Drug Repurposing through miRNA-mRNA Relation

Sharanya Manoharan, Balu Bhasuran, Oviya Ramalakshmi Iyyappan +3

miRNA mRNA relations are closely linked to several biological processes and disease mechanisms In a recent study we tested the performance of large language models LLMs on extracti…

cs.IR2025

Unraveling the Biomarker Prospects of High-Altitude Diseases: Insights from Biomolecular Event Network Constructed using Text Mining

Balu Bhasuran, Sabenabanu Abdulkadhar, Jeyakumar Natarajan

High-altitude diseases (HAD), encompassing acute mountain sickness (AMS), high-altitude cerebral edema (HACE), and high-altitude pulmonary edema (HAPE), are triggered by hypobaric…

cs.CL2025

Lab-AI: Using Retrieval Augmentation to Enhance Language Models for Personalized Lab Test Interpretation in Clinical Medicine

Xiaoyu Wang, Haoyong Ouyang, Balu Bhasuran +5

Accurate interpretation of lab results is crucial in clinical medicine, yet most patient portals use universal normal ranges, ignoring conditional factors like age and gender. This…