2 citations · 3 across the 4 of their papers we have counts for
5 papers
Clinical Validation of Medical-based Large Language Model Chatbots on Ophthalmic Patient Queries with LLM-based Evaluation
Ting Fang Tan, Kabilan Elangovan, Andreas Pollreisz +13
Domain specific large language models are increasingly used to support patient education, triage, and clinical decision making in ophthalmology, making rigorous evaluation essentia…
EVLF-FM: Explainable Vision Language Foundation Model for Medicine
Yang Bai, Haoran Cheng, Yang Zhou +40
Despite the promise of foundation models in medical AI, current systems remain limited - they are modality-specific and lack transparent reasoning processes, hindering clinical ado…
Emerging Semantic Segmentation from Positive and Negative Coarse Label Learning
Le Zhang, Fuping Wu, Arun Thirunavukarasu +3
Large annotated datasets are vital for training segmentation models, but pixel-level labeling is time-consuming, error-prone, and often requires scarce expert annotators, especiall…
Tokenizer: Differentiable Multi-Scale Multi-Modal Tokenizer for Radiology Report Generation
Siyou Li, Pengyao Qin, Huanan Wu +4
Automated radiology report generation (RRG) aims to produce detailed textual reports from clinical imaging, such as computed tomography (CT) scans, to improve the accuracy and effi…
High-performance automated abstract screening with large language model ensembles
Rohan Sanghera, Arun James Thirunavukarasu, Marc El Khoury +7
Large language models (LLMs) excel in tasks requiring processing and interpretation of input text. Abstract screening is a labour-intensive component of systematic review involving…