Artificial intelligence-enabled electrocardiography to triage echocardiography for structural heart disease diagnosis in a low-resource setting.
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| Title: | Artificial intelligence-enabled electrocardiography to triage echocardiography for structural heart disease diagnosis in a low-resource setting. |
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| Authors: | Pedroso AF; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.; Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT, USA., Nascimento BR; Departamento de Clinica Medica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil.; Interventional Cardiology, Hospital Madre Teresa, Belo Horizonte, MG, Brazil.; Congenital Heart Center, Ochsner Children's Hospital, New Orleans, LA, United States., Dhingra LS; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.; Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT, USA., Shankar SV; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.; Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT, USA., Vinhal WC; Centro de Telessaude, Hospital das Clínicas & Departamento de Clinica Medica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil., Reges RBE; Centro de Telessaude, Hospital das Clínicas & Departamento de Clinica Medica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil., Cardoso CS; Centro de Telessaude, Hospital das Clínicas & Departamento de Clinica Medica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil., Sable C; Congenital Heart Center, Ochsner Children's Hospital, New Orleans, LA, United States., Ribeiro ALP; Departamento de Clinica Medica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil.; Centro de Telessaude, Hospital das Clínicas & Departamento de Clinica Medica, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil., Khera R; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.; Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT, USA.; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT, USA.; Department of Biomedical Informatics, Yale School of Medicine, New Haven, CT, USA.; Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. |
| Source: | American journal of preventive cardiology [Am J Prev Cardiol] 2026 Mar 24; Vol. 27, pp. 101539. Date of Electronic Publication: 2026 Mar 24 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier B.V Country of Publication: Netherlands NLM ID: 101769122 Publication Model: eCollection Cited Medium: Internet ISSN: 2666-6677 (Electronic) Linking ISSN: 26666677 NLM ISO Abbreviation: Am J Prev Cardiol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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