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| Application of artificial intelligence-enabled ECG diagnostic models in identifying valvular heart diseases |
| XIE Bingxin, LIU Tong |
| Tianjin Key Laboratory of IonicMolecular Function of Cardiovascular Disease, Department of Cardiology, the Second Hospital of Tianjin Medical University, Tianjin Institute of Cardiology, Tianjin 300211, China |
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Abstract Valvular heart disease (VHD) is a common organic heart disease, and its incidence gradually increases with age. With the crossintegration of artificial intelligence and medical field, artificial intelligence algorithm models have become effective tools for identifying a variety of heart diseases. Artificial intelligenceenabled ECG (AIECG) diagnostic models can identify VHD patients by analyzing their ECG features, which may become an auxiliary tool for the identification of VHD in clinical practice. This paper summarizes the research progress of AIECG diagnostic models in the identification of VHD.
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