Artificial intelligence‐enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes — Krzysztof Irlik (2024) | RDL Network
Artificial intelligence‐enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes
Article 2024 en
Authors
KI
Krzysztof Irlik
HA
Hanadi Aldosari
MH
Mirela Hendel
Abstract
1 min read
Our study highlights the potential of using ML techniques, particularly motifs and discords, to effectively detect dsCAN in patients with diabetes. This approach could be applied in large-scale screening of CAN, particularly to identify definite/severe CAN where cardiovascular risk factor modification may be initiated.
Krzysztof Irlik, Hanadi Aldosari, Mirela Hendel, Hanna Kwiendacz, Julia Piaśnik, Justyna Kulpa, Paweł Ignacy, Sylwia Boczek, Mikołaj Herba, Kamil Kegler, Frans Coenen, Janusz Gumprecht, Yalin Zheng, Professor Gregory Lip, Uazman Alam, Katarzyna Nabrdalik
Krzysztof Irlik, Hanadi Aldosari, Mirela Hendel, Hanna Kwiendacz, Julia Piaśnik, Justyna Kulpa, Paweł Ignacy, Sylwia Boczek, Mikołaj Herba, Kamil Kegler, Frans Coenen, Janusz Gumprecht, Yalin Zheng, Professor Gregory Lip, Uazman Alam, Katarzyna Nabrdalik
Katarzyna Nabrdalik, Krzysztof Irlik, Yanda Meng, Hanna Kwiendacz, Julia Piaśnik, Mirela Hendel, Paweł Ignacy, Justyna Kulpa, Kamil Kegler, Mikołaj Herba, Sylwia Boczek, Effendy Bin Hashim, Zhuangzhi Gao, Janusz Gumprecht, Yalin Zheng, Professor Gregory Lip, Uazman Alam
Serge Masson, Roberto Latini, Giovanni Cioffi, Renato Urso, Tarcisio Vago, Donata Lucci, Gian Francesco Mureddu, Luigi Tarantini, Pompilio Faggiano, Daniela Girfoglio, Mario Velussi, Aldo Maggioni, Carlo Giorda, Marco Comaschi
Discussion(0)
No comments yet. Be the first to comment.