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Showing 1–10 of 10 results
Advanced filters: Author: Ziad Obermeyer Clear advanced filters
  • Optimizing the testing of incoming travellers for COVID-19 involves predicting those who are most likely to test positive. A machine-learning algorithm for targeted testing has been implemented at the Greek border.

    • Ziad Obermeyer
    News & Views
    Nature
    Volume: 599, P: 34-36
  • An algorithmic, machine-learning approach to measuring severe pain from osteoarthritis applied to X-ray images of knees suggests that reported disparities in knee pain in underserved populations can be reduced by comparison with use of standard radiographic measures of disease severity.

    • Emma Pierson
    • David M. Cutler
    • Ziad Obermeyer
    Research
    Nature Medicine
    Volume: 27, P: 136-140
  • Open datasets, curated around unsolved medical problems, are vital to the development of computational research in medicine, but remain in short supply. Nightingale Open Science, a non-profit computing platform, was founded to catalyse research in this nascent field.

    • Sendhil Mullainathan
    • Ziad Obermeyer
    Comments & Opinion
    Nature Medicine
    Volume: 28, P: 897-899
  • Cardiovascular disease (CVD) remains a leading cause of death worldwide, but age-standardized CVD death rates are decreasing steadily. In this Review, Ezzati and colleagues use the available epidemiological data to examine regional and global changes in CVD mortality, as well as trends in smoking, alcohol consumption, diet, physiological risk factors, and improvements in medical care that might underlie these changes.

    • Majid Ezzati
    • Ziad Obermeyer
    • David A. Leon
    Reviews
    Nature Reviews Cardiology
    Volume: 12, P: 508-530
  • Cognitive bias accounts for a significant portion of preventable errors in healthcare, contributing to significant patient morbidity and mortality each year. As large language models (LLMs) are introduced into healthcare and clinical decision-making, these systems are at risk of inheriting – and even amplifying – these existing biases. This article explores both the cognitive biases impacting LLM-assisted medicine and the countervailing strengths these technologies bring to addressing these limitations.

    • Arjun Mahajan
    • Ziad Obermeyer
    • Dylan Powell
    News & ViewsOpen Access
    npj Digital Medicine
    Volume: 8, P: 1-4