11 citations · 27 across the 10 of their papers we have counts for
11 papers
Towards Better Aligned LLM Judges for Radiology Report Evaluation across Modalities and Anatomies
Federica Bologna, Jean-Philippe Corbeil, Matthew Wilkens +1
Current work on radiology report evaluation has focused primarily on LLM-based metrics for chest X-rays (CXR), leaving open whether such approaches remain robust across other modal…
RADAR: A Multimodal Benchmark for 3D Image-Based Radiology Report Review
Zhaoyi Sun, Minal Jagtiani, Wen-wai Yim +4
Radiology reports for the same patient examination may contain clinically meaningful discrepancies arising from interpretation differences, reporting variability, or evolving asses…
BTReport: A Framework for Brain Tumor Radiology Report Generation with Clinically Relevant Features
Juampablo E. Heras Rivera, Dickson T. Chen, Tianyi Ren +4
Recent advances in radiology report generation (RRG) have been driven by large paired image-text datasets; however, progress in neuro-oncology has been limited due to a lack of ope…
DermaVQA-DAS: Dermatology Assessment Schema (DAS) & Datasets for Closed-Ended Question Answering & Segmentation in Patient-Generated Dermatology Images
Wen-wai Yim, Yujuan Fu, Asma Ben Abacha +4
Recent advances in dermatological image analysis have been driven by large-scale annotated datasets; however, most existing benchmarks focus on dermatoscopic images and lack patien…
Overview of the MEDIQA-OE 2025 Shared Task on Medical Order Extraction from Doctor-Patient Consultations
Jean-Philippe Corbeil, Asma Ben Abacha, Jerome Tremblay +4
Clinical documentation increasingly uses automatic speech recognition and summarization, yet converting conversations into actionable medical orders for Electronic Health Records r…
MORQA: Benchmarking Evaluation Metrics for Medical Open-Ended Question Answering
Wen-wai Yim, Asma Ben Abacha, Zixuan Yu +3
Evaluating natural language generation (NLG) systems in the medical domain presents unique challenges due to the critical demands for accuracy, relevance, and domain-specific exper…
Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications
Jean-Philippe Corbeil, Asma Ben Abacha, George Michalopoulos +12
Large language models (LLMs) such as GPT-4o and o1 have demonstrated strong performance on clinical natural language processing (NLP) tasks across multiple medical benchmarks. None…
MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes
Asma Ben Abacha, Wen-wai Yim, Yujuan Fu +4
Several studies showed that Large Language Models (LLMs) can answer medical questions correctly, even outperforming the average human score in some medical exams. However, to our k…
MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging
Noel C. F. Codella, Ying Jin, Shrey Jain +28
In this work, we present MedImageInsight, an open-source medical imaging embedding model. MedImageInsight is trained on medical images with associated text and labels across a dive…
ACI-BENCH: a Novel Ambient Clinical Intelligence Dataset for Benchmarking Automatic Visit Note Generation
Wen-wai Yim, Yujuan Fu, Asma Ben Abacha +3
Recent immense breakthroughs in generative models such as in GPT4 have precipitated re-imagined ubiquitous usage of these models in all applications. One area that can benefit by i…
An Investigation of Evaluation Metrics for Automated Medical Note Generation
Asma Ben Abacha, Wen-wai Yim, George Michalopoulos +1
Recent studies on automatic note generation have shown that doctors can save significant amounts of time when using automatic clinical note generation (Knoll et al., 2022). Summari…