7 papers
MedArena: Comparing LLMs for Medicine-in-the-Wild Clinician Preferences
Eric Wu, Kevin Wu, Jason Hom +11
Large language models (LLMs) are increasingly central to clinician workflows, spanning clinical decision support, medical education, and patient communication. However, current eva…
Merlin: A Computed Tomography Vision-Language Foundation Model and Dataset
Louis Blankemeier, Ashwin Kumar, Joseph Paul Cohen +37
The large volume of abdominal computed tomography (CT) scans coupled with the shortage of radiologists have intensified the need for automated medical image analysis tools. Previou…
Comp2Comp: Open-Source Software with FDA-Cleared Artificial Intelligence Algorithms for Computed Tomography Image Analysis
Adrit Rao, Malte Jensen, Andrea T. Fisher +28
Artificial intelligence allows automatic extraction of imaging biomarkers from already-acquired radiologic images. This paradigm of opportunistic imaging adds value to medical imag…
MedVAL: Toward Expert-Level Medical Text Validation with Language Models
Asad Aali, Vasiliki Bikia, Maya Varma +24
With the growing use of language models (LMs) in clinical environments, there is an immediate need to evaluate the accuracy and safety of LM-generated medical text. Currently, such…
Automated detection of underdiagnosed medical conditions via opportunistic imaging
Asad Aali, Andrew Johnston, Louis Blankemeier +6
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information an…
MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries
François Grolleau, Emily Alsentzer, Timothy Keyes +17
Evaluating factual accuracy in Large Language Model (LLM)-generated clinical text is a critical barrier to adoption, as expert review is unscalable for the continuous quality assur…