Our study suggests that our LLM for DDx has potential to improve clinicians' diagnostic reasoning and accuracy in challenging cases, meriting further real-world evaluation for its ability to empower physicians and widen patients' access to specialist-level expertise. Further, clinicians assisted by our LLM arrived at more comprehensive differential lists than those without its assistance. Comparing the two assisted study arms, the DDx quality score was higher for clinicians assisted by our LLM (top-10 accuracy 51.7%) compared to clinicians without its assistance (36.1%) (McNemar's Test: 45.7, p < 0.01) and clinicians with search (44.4%) (4.75, p = 0.03). Our LLM for DDx exhibited standalone performance that exceeded that of unassisted clinicians (top-10 accuracy 59.1% vs 33.6%, ). All clinicians provided a baseline, unassisted DDx prior to using the respective assistive tools. NEJM Group products, including the New England Journal of Medicine, NEJM Journal Watch, NEJM Knowledge+, NEJM Catalyst, and now NEJM Resident 360, are leaders in providing the medical knowledge and insight that health care providers and leaders need to give their patients the best care. Published continuously for over 200 years, NEJM. Each case report was read by two clinicians, who were randomized to one of two assistive conditions: either assistance from search engines and standard medical resources, or LLM assistance in addition to these tools. The New England Journal of Medicine (NEJM) is the worlds leading medical journal and website. 20 clinicians evaluated 302 challenging, real-world medical cases sourced from the New England Journal of Medicine (NEJM) case reports. At 6 months, participants in the MIND-diet group increased their MIND-diet score by 3.3 points, for a mean score of 11.0, which was maintained at approximately that level throughout the trial. Editorial from The New England Journal of Medicine E-Cigarettes to Assist with Smoking Cessation. In this study, we introduce an LLM optimized for diagnostic reasoning, and evaluate its ability to generate a DDx alone or as an aid to clinicians. The incidence of bioprosthetic-valve failure related to structural valve deterioration was 1.4 in the TAVR group and 2.0 in the surgery group (Table S13). Interactive interfaces powered by Large Language Models (LLMs) present new opportunities to both assist and automate aspects of this process. Download a PDF of the paper titled Towards Accurate Differential Diagnosis with Large Language Models, by Daniel McDuff and Mike Schaekermann and Tao Tu and Anil Palepu and Amy Wang and Jake Garrison and Karan Singhal and Yash Sharma and Shekoofeh Azizi and Kavita Kulkarni and Le Hou and Yong Cheng and Yun Liu and S Sara Mahdavi and Sushant Prakash and Anupam Pathak and Christopher Semturs and Shwetak Patel and Dale R Webster and Ewa Dominowska and Juraj Gottweis and Joelle Barral and Katherine Chou and Greg S Corrado and Yossi Matias and Jake Sunshine and Alan Karthikesalingam and Vivek Natarajan Download PDF Abstract:An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures.
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