Physician- and Patient-Elicited Barriers and Facilitators to Implementation of a Machine Learning-Based Screening Tool for Peripheral Arterial Disease: Preimplementation Study With Physician and Patient Stakeholders.

Ho, Vy; Brown Johnson, Cati; Ghanzouri, Ilies; Amal, Saeed; Asch, Steven; Ross, Elsie

Ho, Vy; Brown Johnson, Cati; Ghanzouri, Ilies; Amal, Saeed; Asch, Steven; Ross, Elsie.

Afiliação

Ho V; Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA, United States.
Brown Johnson C; Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States.
Ghanzouri I; Division of Vascular Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA, United States.
Amal S; College of Engineering, Northeastern University, Boston, MA, United States.
Asch S; Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States.
Ross E; Center for Innovation to Implementation, Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, United States.

JMIR Cardio ; 7: e44732, 2023 Nov 06.

Article em En | MEDLINE | ID: mdl-37930755

Palavras-chave

artificial intelligence; cardiovascular disease; machine learning; peripheral arterial disease; preimplementation study

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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Idioma: En Revista: JMIR Cardio Ano de publicação: 2023 Tipo de documento: Article

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