Artificial intelligence (AI) is increasingly being applied in healthcare, including cardiology, with growing interest in its potential to support diagnosis, prognosis, and clinical decision-making. The rapid pace of technological advancements is not matched by equivalent progress in the regulation and appraisal of th...
Łukasz Kołtowski, M. Basza, M. Soliński et al.· European Heart Journal - Dig...· 0 citations
The findings support tailoring the screening approach to the individual target population in clinical practice, and were independently associated with greater AF detection, particularly in those having single-timepoint screening.
L. Y. Xing, W. F. McIntyre, J. Engdahl et al.· Europace· 0 citations
Screening-detected atrial fibrillation is associated with a high risk of heart failure, comparable to known atrial fibrillation, and is not a benign condition.
G. Sado, C. Bonander, Katrin Kemp Gudmundsdottir et al.· Europace· 0 citations
The EHR-based machine learning model, FIND-AF 2.0, identifies a high-risk subpopulation for AF diagnosis among patients at elevated risk of stroke and could enable scalable, EHR-driven, risk-guided AF screening.
R. Nadarajah, Jianhua Wu, A. Wahab et al.· Circulation· 0 citations
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