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Prediction Models - Development, Evaluation, and Clinical Application

delete2020-04-23
delete77
PRE
AI
M
Michael Pencina *
B
Benjamin A. Goldstein
R
Ralph B. D’Agostino
DOI:10.1056/NEJMp2000589delete
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Abstract

Abstract

En 中文
Prediction models' newfound importance and the emergence of model development based on machine learning raise questions about how to ensure their safety and efficacy, given their growing role in risk stratification, care pathways, and clinical outcomes.
Keywords:
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

New England Journal of Medicine cover
New England Journal of Medicine
IF:
78.5
Papers:
2.7W
Citations:
39.7W

Organization

D
Duke University
Scholars:
6.3W
Papers: 5.7W
Citations: 6.5W
B
boston university
Scholars:
3.8W
Papers: 3.2W
Citations: 67
Cited Papers

Cited Papers

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
err2019-06-01
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errChristodoulou, Evangelia; Ma, Jie; Collins, Gary S.; Steyerberg, Ewout W.; Verbakel, Jan Y.; Van Calster, Ben
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2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines
err2014-06-24
err2.3K
errOAAI
errGoff, David C., Jr.; Lloyd-Jones, Donald M.; Bennett, Glen; Coady, Sean; D'Agostino, Ralph B.; Gibbons, Raymond; Greenland, Philip; Lackland, Daniel T.; Levy, Daniel; O'Donnell, Christopher J.; Robinson, Jennifer G.; Schwartz, J. Sanford; Shero, Susan T.; Smith, Sidney C., Jr.; Sorlie, Paul; Stone, Neil J.; Wilson, Peter W. F.
errShare
errSave
Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement
err2015-01-06
err7.7K
errOAAI
errCollins, Gary S.; Reitsma, Johannes B.; Altman, Douglas G.; Moons, Karel G. M.
errShare
errSave