A Machine Learning Approach to Developing an Accurate Prediction of Maximal Heart Rate During Exercise Testing in Apparently Healthy Adults.

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Title:	A Machine Learning Approach to Developing an Accurate Prediction of Maximal Heart Rate During Exercise Testing in Apparently Healthy Adults.
Authors :	V. Marković
Issue Date:	2023
Publication:	Journal of Cardiopulmonary Rehabilitation and Prevention
ISSN :	1932-751x Search Idenfier
Type:	Article
Collation:	vol. 43 br. 5 str. 377-383
DOI:	10.1097/hcr.0000000000000786
WoS-ID:	001055642300010
Scopus-ID:	2-s2.0-85168785795
URI:	https://enauka.gov.rs/handle/123456789/763355 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/11341 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/9486 https://journals.lww.com/jcrjournal/abstract/2023/09000/a_machine_learning_approach_to_developing_an.9.aspx
Project:	FRIEND Consortium Contributors: Ball State University (Matthew Harber, Leonard Kaminsky, and Mitchell Whaley), Brooke Army Medical Center (Kenneth Leclerc), Johns Hopkins University (Kerry Stewart), Southern Connecticut State University (Robert Axtell), an FRIEND Consortium Contributors: Ball State University Brooke Army Medical Center University of Tennessee, Knoxville (David Bassett)
M-category:	21M21

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