Artificial intelligence approach improves ischaemia prediction beyond the known pretest probability scores

نویسندگان

چکیده

Abstract Background Pre-test probability (PTP) assessment is crucial in the of patients with suspected ischaemia/coronary artery disease. Presently there no established role for artificial intelligence estimating PTP. Purpose Comparison a recently developed memetic pattern based algorithm (MPA) diagnostic power scores predicting ischaemia on positron emission tomography myocardial perfusion imaging (PET MPI). Methods Consecutive undergoing Rubidium PET MPI routine clinical evaluation were included. The PTP each patient was estimated by MPA, Diamond and Forrester (DFS), models from European Society Cardiology Guidelines 2013 (ESC 2013) 2019 2019) Framingham (FRS). studies assessed presence ischaemia. Ischaemia defined as summed difference score (SDS) ≥2. Results mean age 531 66±11 years, 34% female, 50% had known prior coronary disease; 208 evidence No found 323 patients. areas under curve (AUC) are shown figure. MPA provided an AUC 0.76, 0.67, DFS 0.56, FRS 0.68. Conclusion outperforms ESC, prediction MPI. It has potential to improve accuracy CAD Funding Acknowledgement Type funding sources: Public grant(s) – National budget only. Main source(s): study part funded Swiss Heart Foundation.

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ژورنال

عنوان ژورنال: European Heart Journal

سال: 2021

ISSN: ['2634-3916']

DOI: https://doi.org/10.1093/eurheartj/ehab724.1182