TY - JOUR
T1 - Artificial Intelligence in Cardiology
T2 - Present and Future
AU - Lopez-Jimenez, Francisco
AU - Attia, Zachi
AU - Arruda-Olson, Adelaide M.
AU - Carter, Rickey
AU - Chareonthaitawee, Panithaya
AU - Jouni, Hayan
AU - Kapa, Suraj
AU - Lerman, Amir
AU - Luong, Christina
AU - Medina-Inojosa, Jose R.
AU - Noseworthy, Peter A.
AU - Pellikka, Patricia A.
AU - Redfield, Margaret M.
AU - Roger, Veronique L.
AU - Sandhu, Gurpreet S.
AU - Senecal, Conor
AU - Friedman, Paul A.
N1 - Publisher Copyright:
© 2020 Mayo Foundation for Medical Education and Research
PY - 2020/5
Y1 - 2020/5
N2 - Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel.
AB - Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel.
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U2 - 10.1016/j.mayocp.2020.01.038
DO - 10.1016/j.mayocp.2020.01.038
M3 - Review article
C2 - 32370835
AN - SCOPUS:85083881628
SN - 0025-6196
VL - 95
SP - 1015
EP - 1039
JO - Mayo Clinic proceedings
JF - Mayo Clinic proceedings
IS - 5
ER -