Heart disease risk diagnosis method based on deep convolutional neural network model

Abstract

The invention relates to a heart disease risk diagnosis method based on a deep convolutional neural network model. The method comprises the following steps: building a heart disease risk prediction model based on a deep convolutional neural network, and carrying out training, learning and testing; acquiring an electrocardiogram and a cardiogram of a user by using a wearable device; comparing the electrocardiogram and the cardiogram of the user, and identifying electrocardiogram feature points and cardiogram feature points of the specific event occurrence time of the cardiac impulse cycle; calculating a time interval value of any two feature points to obtain a plurality of feature values, and calculating a plurality of physiological indexes according to the plurality of feature values; outputting the heart disease risk probability corresponding to the physiological indexes through a DCNN model according to each input physiological index; calculating a heart disease risk comprehensive probability value of the user by adopting a formula; and judging the heart disease risk level of the user according to the heart disease risk comprehensive probability value. According to the invention,the risk probability of cardiac acute diseases of the user can be predicted in real time.

Description

technical field [0001] The invention relates to the field of medical technology, in particular to a heart attack risk diagnosis method based on a deep convolutional neural network model. Background technique [0002] Heart disease, especially acute heart disease such as cardiovascular disease, has always been one of the top ten causes of death for middle-aged and elderly people. In case of an acute heart disease, since the development of medical care in our country is still in an immature stage, even if someone calls 120 in time, the hospital may not be able to rush to the scene immediately for rescue work, and the golden time for rescue of patients with the disease is often only a few tens of minutes Once this golden rescue time is exceeded, it may lead to myocardial cell necrosis or heart failure in patients. Therefore, it is particularly necessary to carry out a certain degree of early warning for acute cardiac diseases. [0003] At present, with the development of medic...

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Problems solved by technology

[0003] At present, with the development of medical technology, middle-aged and elderly people in most cities can get regular physical examinations, and can detect acute cardiac diseases before the onset to a certain extent. However, this method still requires patients to actively and regularly Go to the hospital for physical examination, considering that most medium and large hospitals are overcrowded, whether in large cities or small cities, and small hospitals or community hospitals cannot provide patients with satisfactory and reassuring levels of medical care. At the same time, whether acute heart disease The onset of the disease requires long-term, uninterrupted clinical observation. Therefore, the active warning work before the onset of acute cardiac diseases cannot be well realized in the prior art.

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