56 citations · 61 across the 8 of their papers we have counts for
9 papers
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…
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,…
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…
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…
Evaluating the Impact of Lab Test Results on Large Language Models Generated Differential Diagnoses from Clinical Case Vignettes
Balu Bhasuran, Qiao Jin, Yuzhang Xie +6
Differential diagnosis is crucial for medicine as it helps healthcare providers systematically distinguish between conditions that share similar symptoms. This study assesses the i…
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…
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…
Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study
Zhe He, Balu Bhasuran, Qiao Jin +6
Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We…
Literature Based Discovery (LBD): Towards Hypothesis Generation and Knowledge Discovery in Biomedical Text Mining
Balu Bhasuran, Gurusamy Murugesan, Jeyakumar Natarajan
Biomedical knowledge is growing in an astounding pace with a majority of this knowledge is represented as scientific publications. Text mining tools and methods represents automati…