The National Institutes of Health funding for clinical research applying machine learning techniques in 2017

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作者：
Amarnath R. Annapureddy
Suveen Angraal
Cesar Caraballo
Alyssa Grimshaw
Chenxi Huang
Bobak J. Mortazavi
Harlan M. Krumholz
机构：
[1] Yale-New Haven Hospital,Center for Outcomes Research and Evaluation
[2] Yale School of Medicine,Section of Cardiovascular Medicine, Department of Internal Medicine
[3] University of Missouri Kansas City School of Medicine,Department of Internal Medicine
[4] Yale University,Harvey Cushing/John Hay Whitney Medical Library
[5] Texas A&M University,Department of Computer Science & Engineering
[6] Yale School of Public Health,Department of Health Policy and Management
来源：
npj Digital Medicine | / 3卷
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摘要：
Machine learning (ML) techniques have become ubiquitous and indispensable for solving intricate problems in most disciplines. To determine the extent of funding for clinical research projects applying ML techniques by the National Institutes of Health (NIH) in 2017, we searched the NIH Research Portfolio Online Reporting Tools Expenditures and Results (RePORTER) system using relevant keywords. We identified 535 projects, which together received a total of $264 million, accounting for 2% of the NIH extramural budget for clinical research.
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