Electrocardiogram analysis method and device

Abstract

The invention relates to the technical field of image processing, in particular to an electrocardiogram analysis method and device. In order to solve the problem of lack of high-quality medical annotation and lack of interpretability auxiliary analysis in the prior art, the method of the present invention includes obtaining the text semantic information corresponding to each electrocardiogram through the text semantic information extraction model based on multiple electrocardiograms obtained in advance vector; based on a plurality of electrocardiograms, the electrocardiogram waveform vector corresponding to each electrocardiogram is obtained through the electrocardiogram waveform vector extraction model; according to the text semantic information vector, the electrocardiogram waveform vector and the first event set obtained in advance, the first electrocardiogram analysis result is obtained; Obtain a second electrocardiogram analysis result according to the text semantic information vector and the electrocardiogram waveform vector; obtain an electrocardiogram event corresponding to each electrocardiogram according to the first electrocardiogram analysis result and the second electrocardiogram analysis result. The method of the invention can directly interpret the electrocardiogram in PDF format.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an electrocardiogram analysis method and device. Background technique [0002] Since its birth, electrocardiography (ECG) examination technology has been widely used in clinical health examinations in cardiovascular and other fields because of its simple, efficient and non-invasive characteristics. Traditional ECG machines can generate ECG reports that include basic information such as ECG signal waveforms and rhythms; human physicians can give specific insights into ECG reports based on comprehensive analysis of patient age, signs, medical history, etc., as well as medical knowledge and case experience. judge. Electrocardiogram examination has a large business volume in hospitals at all levels. However, medical resources in my country are relatively scarce and severely unevenly distributed. There is a shortage of experienced electrocardiogram physicians in primary hosp...

AI Technical Summary

Problems solved by technology

One is the scarcity of high-quality medical annotations: for rare ECG events, it is very difficult to collect enough training samples, and end-to-end models such as complex neural networks tend to overfit the ECG in the training set, even if obtained on the experimental data. Although it has achieved good results, it is still difficult to guarantee the generalization ability of patients in real complex environments

The second is the lack of interpretability of auxiliary analysis: modern evidence-based medicine attaches great importance to giving evidence for diagnosis, while the existing public end-to-end artificial intelligence diagnosis model can only directly give the probability of specific ECG events, human physicians It is difficult to efficiently verify and confirm the judgments given by such machines, which makes these systems limited in clinical scenarios with high safety requirements

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