1. Bernstein and colleagues evaluated potential jurors’ perception of culpability of a radiologist in a hypothetical false-negative diagnosis malpractice case. ...
1. Jaeckle and colleagues assessed the performance of machine learning models to diagnose celiac disease based on duodenal biopsies. 2. ...
1. Kazemzadeh and colleagues evaluated the performance of AI systems that detect TB and chest X-ray abnormalities against that of ...
1. Liu and colleagues compared efficiency between two groups of clinicians, with one group using an artificial intelligence (AI)-powered documentation ...
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1. Upton and colleagues assessed the appropriateness of coronary angiography referrals made by clinicians working independently or with an AI ...
1. Kamran and colleagues used a retrospective inpatient cohort to evaluate the Epic sepsis model (ESM)’s ability to predict sepsis ...
1. Patel and colleagues conducted a secondary economic analysis of a trial that assigned high-risk cancer patients to serious illness ...
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1. A randomized controlled trial by Lin and colleagues compared artificial intelligence (AI) to standard care in triaging suspected cases ...
1. Unlu and colleagues compared RECTIFIER, a large language model (LLM), against human study staff to evaluate patient eligibility for ...
