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Showing 1–6 of 6 results
Advanced filters: Author: Sendhil Mullainathan Clear advanced filters

  • 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

  • A massive field study whereby many different treatments are tested synchronously in one large sample using a common objectively measured outcome, termed a megastudy, was performed to examine the ability of interventions to increase gym attendance by American adults.

    • Katherine L. Milkman
    • Dena Gromet
    • Angela L. Duckworth
    Research
    Nature
    Volume: 600, P: 478-483

  • Algorithms are designed to learn user preferences by observing user behaviour. This causes algorithms to fail to reflect user preferences when psychological biases affect user decision making. For algorithms to enhance social welfare, algorithm design needs to be psychologically informed.

    • Carey K. Morewedge
    • Sendhil Mullainathan
    • Jens O. Ludwig
    Comments & Opinion
    Nature Human Behaviour
    Volume: 7, P: 1822-1824

  • 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

  • The combination of computational and social sciences requires the integration of explanatory and predictive approaches into ‘integrative modelling’, according to Hofman and colleagues.

    • Jake M. Hofman
    • Duncan J. Watts
    • Tal Yarkoni
    Reviews
    Nature
    Volume: 595, P: 181-188