Your browser doesn't support javascript.
loading
Advances in Diagnosis, Therapy, and Prognosis of Coronary Artery Disease Powered by Deep Learning Algorithms.
Chu, Miao; Wu, Peng; Li, Guanyu; Yang, Wei; Gutiérrez-Chico, Juan Luis; Tu, Shengxian.
Afiliação
  • Chu M; Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Wu P; Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Li G; Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
  • Yang W; Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.
  • Gutiérrez-Chico JL; School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.
  • Tu S; Bundeswehrzentralkrankenhaus (Federal Army Central Military Hospital), Koblenz, Germany.
JACC Asia ; 3(1): 1-14, 2023 Feb.
Article em En | MEDLINE | ID: mdl-36873752
ABSTRACT
Percutaneous coronary intervention has been a standard treatment strategy for patients with coronary artery disease with continuous ebullient progress in technology and techniques. The application of artificial intelligence and deep learning in particular is currently boosting the development of interventional solutions, improving the efficiency and objectivity of diagnosis and treatment. The ever-growing amount of data and computing power together with cutting-edge algorithms pave the way for the integration of deep learning into clinical practice, which has revolutionized the interventional workflow in imaging processing, interpretation, and navigation. This review discusses the development of deep learning algorithms and their corresponding evaluation metrics together with their clinical applications. Advanced deep learning algorithms create new opportunities for precise diagnosis and tailored treatment with a high degree of automation, reduced radiation, and enhanced risk stratification. Generalization, interpretability, and regulatory issues are remaining challenges that need to be addressed through joint efforts from multidisciplinary community.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: JACC Asia Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: JACC Asia Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China