Publications (13)
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…
Overview of the First Shared Task on Clinical Text Generation: RRG24 and "Discharge Me!"
Justin Xu, Zhihong Chen, Andrew Johnston +9
Recent developments in natural language generation have tremendous implications for healthcare. For instance, state-of-the-art systems could automate the generation of sections in…
First, do NOHARM: a medical safety benchmark and randomized study of physician and AI teaming on clinical consultations
David Wu, Fateme Nateghi Haredasht, Saloni Kumar Maharaj +54
The paper introduces NOHARM, a benchmark of 1,100 primary‑care to specialist consultation cases, to evaluate how often large language models and retrieval‑augmented clinical AI too…
Deployment and Evaluation of an EHR-integrated, Large Language Model-Powered Tool to Triage Surgical Patients
Jane Wang, Timothy Keyes, April S Liang +10
Surgical co-management (SCM) is an evidence-based model in which hospitalists jointly manage medically complex perioperative patients alongside surgical teams. Despite its clinical…
SmartAlert: Implementing Machine Learning-Driven Clinical Decision Support for Inpatient Lab Utilization Reduction
April S. Liang, Fatemeh Amrollahi, Yixing Jiang +21
Repetitive laboratory testing unlikely to yield clinically useful information is a common practice that burdens patients and increases healthcare costs. Education and feedback inte…
Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization
Dave Van Veen, Cara Van Uden, Louis Blankemeier +16
Analyzing vast textual data and summarizing key information from electronic health records imposes a substantial burden on how clinicians allocate their time. Although large langua…
Superhuman performance of a large language model on the reasoning tasks of a physician
Peter G. Brodeur, Thomas A. Buckley, Zahir Kanjee +22
A seminal paper published by Ledley and Lusted in 1959 introduced complex clinical diagnostic reasoning cases as the gold standard for the evaluation of expert medical computing sy…
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…
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…
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…
A dataset and benchmark for hospital course summarization with adapted large language models
Asad Aali, Dave Van Veen, Yamin Ishraq Arefeen +9
Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automati…