Predicting the future-big data, machine learning, and clinical medicine

New England Journal of Medicine

Volumn 375, Issue 13, 2016, Pages 1216-1219

  Obermeyer, Ziad ^a   Emanuel, Ezekiel J ^b  

^a HARVARD MEDICAL SCHOOL   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APACHE; CLINICAL MEDICINE; DATA ANALYSIS; DATA BASE; DIAGNOSTIC ERROR; ELECTRONIC HEALTH RECORD; HUMAN; LEARNING ALGORITHM; MACHINE LEARNING; MEASUREMENT ACCURACY; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; REVIEW; SEQUENTIAL ORGAN FAILURE ASSESSMENT SCORE; STATISTICAL MODEL; ALGORITHM; BIOLOGY; DIAGNOSIS; EXPERT SYSTEM;

ALGORITHMS; CLINICAL MEDICINE; COMPUTATIONAL BIOLOGY; DIAGNOSIS; EXPERT SYSTEMS; MACHINE LEARNING; PROGNOSIS;

EID: 84990046464     PISSN: 00284793     EISSN: 15334406     Source Type: Journal    
DOI: 10.1056/NEJMp1606181     Document Type: Review

References (5)

1. Mullainathan S, Spiess J. Machine learning: an applied econometric approach. J Econ Perspect (in press).
2. Halevy A, Norvig P, Pereira F. The unreasonable effectiveness of data. IEEE Intell Syst 2009;24(2):8-12.
3. Kleinberg J, Ludwig J, Mullainathan S, Obermeyer Z. Prediction policy problems. Am Econ Rev 2015; 105: 491-5.
4. Bouton CE, Shaikhouni A, Annetta NV, et al. Restoring cortical control of functional movement in a human with quadriplegia. Nature 2016;533:247-50.
5. Gilbert FJ, Astley SM, Gillan MGC, et al. Single reading with computer-aided detection for screening mammography. N Engl J Med 2008;359:1675-84.