32 citations · 48 across the 21 of their papers we have counts for
9 papers · 1 filter
Graph-based LLM over Semi-Structured Population Data for Dynamic Policy Response
Daqian Shi, Xiaolei Diao, Jinge Wu +4
Timely and accurate analysis of population-level data is crucial for effective decision-making during public health emergencies such as the COVID-19 pandemic. However, the massive…
HARE: an entity and relation centric evaluation framework for histopathology reports
Yunsoo Kim, Michal W. S. Ong, Alex Shavick +2
Medical domain automated text generation is an active area of research and development; however, evaluating the clinical quality of generated reports remains a challenge, especiall…
RadEyeVideo: Enhancing general-domain Large Vision Language Model for chest X-ray analysis with video representations of eye gaze
Yunsoo Kim, Jinge Wu, Honghan Wu
Large Vision-Language Models (LVLMs) have demonstrated promising performance in chest X-ray (CXR) analysis. To enhance human-computer interaction, several studies have incorporated…
Adverse Event Extraction from Discharge Summaries: A New Dataset, Annotation Scheme, and Initial Findings
Imane Guellil, Salomé Andres, Atul Anand +5
In this work, we present a manually annotated corpus for Adverse Event (AE) extraction from discharge summaries of elderly patients, a population often underrepresented in clinical…
BioHopR: A Benchmark for Multi-Hop, Multi-Answer Reasoning in Biomedical Domain
Yunsoo Kim, Yusuf Abdulle, Honghan Wu
Biomedical reasoning often requires traversing interconnected relationships across entities such as drugs, diseases, and proteins. Despite the increasing prominence of large langua…
Look & Mark: Leveraging Radiologist Eye Fixations and Bounding boxes in Multimodal Large Language Models for Chest X-ray Report Generation
Yunsoo Kim, Jinge Wu, Su-Hwan Kim +3
Recent advancements in multimodal Large Language Models (LLMs) have significantly enhanced the automation of medical image analysis, particularly in generating radiology reports fr…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
IHC-LLMiner: Automated extraction of tumour immunohistochemical profiles from PubMed abstracts using large language models
Yunsoo Kim, Michal W. S. Ong, Daniel W. Rogalsky +3
Immunohistochemistry (IHC) is essential in diagnostic pathology and biomedical research, offering critical insights into protein expression and tumour biology. This study presents…
RiskAgent: Synergizing Language Models with Validated Tools for Evidence-Based Risk Prediction
Fenglin Liu, Jinge Wu, Hongjian Zhou +9
Large Language Models (LLMs) achieve competitive results compared to human experts in medical examinations. However, it remains a challenge to apply LLMs to complex clinical decisi…