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Intelligent prediction method for fusing fundus color pictures and deep learning myocardial infarction

An intelligent prediction and color photo technology, applied in the fields of ophthalmoscopy, medical science, medical imaging, etc., can solve the problem of no effective prediction method, cost a lot of manpower and material resources, etc., achieve efficient time series prediction, reduce pain and inconvenience, and classify accurately. Effect

Inactive Publication Date: 2019-11-22
ZHONGSHAN OPHTHALMIC CENT SUN YAT SEN UNIV
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Problems solved by technology

At home and abroad, similar adverse event prediction models have been done, but there is no effective prediction method yet
Studies have shown that cardiovascular diseases can be effectively predicted by observing the distribution of blood vessels, vascular diameters and lesions in the retina; however, the traditional semi-automatic mode to outline fundus blood vessels and lesions requires a lot of manpower and material resources and is subjective

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  • Intelligent prediction method for fusing fundus color pictures and deep learning myocardial infarction

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Embodiment Construction

[0029] The present invention is further described in conjunction with the following examples.

[0030] Such as figure 1 Shown, the present invention is further described in conjunction with the following examples.

[0031] An intelligent prediction method for myocardial infarction that integrates fundus color photos and width learning in this embodiment includes the following steps:

[0032] S1: Using the longitudinal follow-up data in the database, based on whether the patient has myocardial infarction, the color fundus photo is marked and image preprocessed to obtain a training set; the training set is a training set for obtaining the relationship between the color fundus photo and myocardial infarction.

[0033] S2: Build a breadth learning network based on fundus color photos;

[0034] S3: train the parameters of the width learning network;

[0035] S4: Through the width learning network, learn and extract the fundus characteristics of patients with myocardial infarctio...

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Abstract

The invention relates to the technical field of artificial intelligence, in particular to an intelligent prediction method for fusing fundus color pictures and deep learning myocardial infarction. Themethod comprises the specific steps of labelling and preprocessing collected fundus color pictures on the basis of longitudinal follow-up visiting data of a database; constructing a deep learning network, and optimizing deep parameters; obtaining patient fundus color pictures to be recognized, utilizing a deep learning intelligent model for recognizing fundus characteristics, and obtaining an intelligent classification result for judging whether or not myocardial infarction exists in the fundus color pictures; the method can efficiently, conveniently and non-invasively perform myocardial infarction high-risk group screening.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to an intelligent prediction method for myocardial infarction which combines fundus color photos and width learning. Background technique [0002] Myocardial infarction generally refers to acute myocardial infarction, that is, myocardial cell damage or even necrosis caused by acute and persistent ischemia and hypoxia caused by coronary artery disease. Clinical symptoms include retrosternal pain, which may be complicated by myocardial rupture, mural thrombus, arrhythmia, cardiogenic shock, etc., which can be life-threatening and have a high morbidity rate. Myocardial infarction is most common in Europe and the United States, and about 1.5 million people in the United States have myocardial infarction every year. In recent years, it has shown an obvious upward trend in China, with more than 500,000 new cases each year and at least 2 million existing patients. For myo...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B3/12
CPCA61B3/12A61B2576/02
Inventor 何明光李治玺
Owner ZHONGSHAN OPHTHALMIC CENT SUN YAT SEN UNIV
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