13 papers
Clin-JEPA: A Multi-Phase Co-Training Framework for Joint-Embedding Predictive Pretraining on EHR Patient Trajectories
Yixuan Yang, Mehak Arora, Ryan Zhang +10
We present Clin-JEPA, a multi-phase co-training framework for joint-embedding predictive (JEPA) pretraining on EHR patient trajectories. JEPA architectures have enabled latent-spac…
Planner-Auditor Twin: Agentic Discharge Planning with FHIR-Based LLM Planning, Guideline Recall, Optional Caching and Self-Improvement
Kaiyuan Wu, Aditya Nagori, Rishikesan Kamaleswaran
Objective: Large language models (LLMs) show promise for clinical discharge planning, but their use is constrained by hallucination, omissions, and miscalibrated confidence. We int…
SpikGPT: A High-Accuracy and Interpretable Spiking Attention Framework for Single-Cell Annotation
Min Huang, Rishikesan Kamaleswaran
Accurate and scalable cell type annotation remains a challenge in single-cell transcriptomics, especially when datasets exhibit strong batch effects or contain previously unseen ce…
Performance of Large Language Models in Answering Critical Care Medicine Questions
Mahmoud Alwakeel, Aditya Nagori, An-Kwok Ian Wong +3
Large Language Models have been tested on medical student-level questions, but their performance in specialized fields like Critical Care Medicine (CCM) is less explored. This stud…
Open-Source Agentic Hybrid RAG Framework for Scientific Literature Review
Aditya Nagori, Ricardo Accorsi Casonatto, Ayush Gautam +2
The surge in scientific publications challenges traditional review methods, demanding tools that integrate structured metadata with full-text analysis. Hybrid Retrieval Augmented G…
Evaluating LLMs in Medicine: A Call for Rigor, Transparency
Mahmoud Alwakeel, Aditya Nagori, Vijay Krishnamoorthy +1
Objectives: To evaluate the current limitations of large language models (LLMs) in medical question answering, focusing on the quality of datasets used for their evaluation. Materi…