Risk prediction for individuals

JAMA - Journal of the American Medical Association

Volumn 314, Issue 17, 2015, Pages 1875-

  Van Calster, Ben ^a   Steyerberg, Ewout W ^b   Harrell, Frank H ^c  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b ERASMUS MEDICAL CENTER   (Netherlands)

^c VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGE; CANCER PATIENT; CANCER RECURRENCE; CANCER RISK; EXPERIENCE; HUMAN; LETTER; MEDICAL DECISION MAKING; NON INVASIVE PROCEDURE; OUTCOME ASSESSMENT; PREDICTION; PRIORITY JOURNAL; RISK ASSESSMENT; ALGORITHM; PHYSICIAN ATTITUDE;

ALGORITHMS; HUMANS; PHYSICIAN'S ROLE; RISK ASSESSMENT;

EID: 84946064046     PISSN: 00987484     EISSN: 15383598     Source Type: Journal    
DOI: 10.1001/jama.2015.12215     Document Type: Letter

References (5)

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3. Silver N. The Signal and the Noise: Why So Many Predictions Fail-But Some Don't. New York, NY: Penguin Press; 2012.
4. Siegel E. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Hoboken, NJ: John Wiley & Sons; 2013.
5. Van Calster B, Vickers AJ. Calibration of risk prediction models: impact on decision-Analytic performance. Med Decis Making. 2015;35(2):162-169.