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In an order of the abstract structure of the human body from inside to outside, this paper lists the state-of-the-art research advances of artificial intelligence (AI) especially deep neural network in ECG analysis from aspects of electrical conduction system and the structure of the heart ( including heart valves, myocardium, coronary arteries, etc. ), other systems out of the heart, ect. This paper introduces the application of AI-enabled ECG analysis technology in identifying arhythmias, electrolyte disturbances, valvular heart disease, coronary heart disease, and diseases of the circulation system and digestive system. This paper also covers its innovative application in the field of personal identification, and how to use AI technologies such as transfer learning in practical research. This paper is aimed to promote more cross-field cooperations, explore deep values of ECG, and help to realize the screening, diagnosis and treatment of multi-system diseases. [ABSTRACT FROM AUTHOR]

Since the outbreak of corona virus disease 2019, deep learning has been widely used in predicting epidemic trends, screening high-risk groups and making early diagnosis. Novel coronavirus infection mainly causes pulmonary diseases, and also affects cardiovascular system, resulting in electrocardiogram (ECG) abnormalities. ECG tracking image technology is a hot spot in the research of deep learning. Compared with traditional ECG judgment methods, its accuracy and sensitivity are both higher. It can be used in the effective diagnosis, clinical decision-making and prognosis evaluation of patients with novel coronavirus infection. This paper reviews on the ECG changes after novel coronavirus infection, and the advances of ECG tracking image technology applied in the auxiliary diagnosis of novel coronavirus infection, so as to provide references for clinical healthcare workers. [ABSTRACT FROM AUTHOR]