9 papers
Tree-of-Evidence: Efficient "System 2" Search for Faithful Multimodal Grounding
Micky C. Nnamdi, Benoit L. Marteau, Yishan Zhong +2
Large Multimodal Models (LMMs) achieve state-of-the-art performance in high-stakes domains like healthcare, yet their reasoning remains opaque. Current interpretability methods, su…
RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation
Jieru Li, Matthew Chen, Micky C. Nnamdi +3
Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degrades under realistic image c…
EvidenceRL: Reinforcing Evidence Consistency for Trustworthy Language Models
J. Ben Tamo, Yuxing Lu, Benoit L. Marteau +2
Large Language Models (LLMs) are fluent but prone to hallucinations, producing answers that appear plausible yet are unsupported by available evidence. This failure is especially p…
Advancing Problem-Based Learning in Biomedical Engineering in the Era of Generative AI
Micky C. Nnamdi, J. Ben Tamo, Benoit Marteau +2
Problem-Based Learning (PBL) has significantly impacted biomedical engineering (BME) education since its introduction in the early 2000s, effectively enhancing critical thinking an…
Benchmarking LLM Summaries of Multimodal Clinical Time Series for Remote Monitoring
Aditya Shukla, Yining Yuan, Ben Tamo +7
Large language models (LLMs) can generate fluent clinical summaries of remote therapeutic monitoring time series. However, it remains unclear whether these narratives faithfully ca…
Monocular Markerless Motion Capture Enables Quantitative Assessment of Upper Extremity Reachable Workspace
Seth Donahue, J. D. Peiffer, R. Tyler Richardson +7
To validate a clinically accessible approach for quantifying the Upper Extremity Reachable Workspace (UERW) using a single (monocular) camera and Artificial Intelligence (AI)-drive…