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An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction
Publication date: Available online 1 August 2019Source: The LancetAuthor(s): Zachi I Attia, Peter A Noseworthy, Francisco Lopez-Jimenez, Samuel J Asirvatham, Abhishek J Deshmukh, Bernard J Gersh, Rickey E Carter, Xiaoxi Yao, Alejandro A Rabinstein, Brad J Erickson, Suraj Kapa, Paul A FriedmanSummaryBackgroundAtrial fibrillation is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death. Existing screening methods require prolonged monitoring and are limited by cost and low yield. We aimed to develop a rapid, inexpensive, point-of-care means of identifying patients with atrial ...
Source: The Lancet - August 2, 2019 Category: General Medicine Source Type: research

Social bias in artificial intelligence algorithms designed to improve cardiovascular risk assessment relative to the Framingham Risk Score: a protocol for a systematic review
This study will employ an equity-lens to identify sources of bias (ie, race/ethnicity, gender and social stratum) in ML algorithms designed to improve CVD risk assessment relative to the FRS. A comprehensive literature search will be completed using MEDLINE, Embase and IEEE to answer the research question: do AI algorithms that are designed for the estimation of CVD risk and that compare performance with the FRS address the sources of bias inherent in the FRS? No study date filters will be imposed on the search, but English language filters will be applied. Studies describing a specific algorithm or ML approach that provid...
Source: BMJ Open - May 31, 2023 Category: General Medicine Authors: Garcha, I., Phillips, S. P. Tags: Open access, General practice / Family practice Source Type: research