Machine Learning Algorithms: Selection of Appropriate Validation Populations for Cardiology Research-Be Careful!
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| Title: | Machine Learning Algorithms: Selection of Appropriate Validation Populations for Cardiology Research-Be Careful! |
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| Authors: | Sanders WE Jr; CorVista Health, Inc, Washington, DC, USA; University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Electronic address: wsanders@corvista.com., Khedraki R; Scripps Clinic, San Diego, California, USA., Rabbat M; Loyola University Medical Center, Maywood, Illinois, USA., McMinn TR; Austin Heart, Austin, Texas, USA., Burton T; CorVista Health(†), Toronto, Ontario, Canada., Khosousi A; CorVista Health(†), Toronto, Ontario, Canada., Fathieh F; CorVista Health(†), Toronto, Ontario, Canada., Gillins HR; CorVista Health, Inc, Washington, DC, USA., Ramchandani S; CorVista Health(†), Toronto, Ontario, Canada., Shadforth IP; CorVista Health, Inc, Washington, DC, USA. |
| Source: | JACC. Advances [JACC Adv] 2023 Jan 11; Vol. 2 (1), pp. 100166. Date of Electronic Publication: 2023 Jan 11 (Print Publication: 2023). |
| Publication Type: | Editorial |
| Journal Info: | Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918419284106676 Publication Model: eCollection Cited Medium: Internet ISSN: 2772-963X (Electronic) Linking ISSN: 2772963X NLM ISO Abbreviation: JACC Adv Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2772-963X |
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| DOI: | 10.1016/j.jacadv.2022.100166 |
