Coronary heart disease risk prediction method based on multi-modal data and related equipment
A risk prediction, coronary heart disease technology, applied in the medical field, can solve problems such as difficult to obtain predictable results
Active Publication Date: 2020-12-01
PING AN TECH (SHENZHEN) CO LTD
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Problems solved by technology
At present, there is also an intelligent prediction system for coronary heart disease. However, this system can only process a single type of data and a small amount of data. It is difficult to obtain good prediction results for large-scale multi-modal data.
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[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0057] The coronary heart disease risk prediction method based on multimodal data provided by the embodiments of the present invention can be applied to a coronary heart disease prediction system. In some embodiments, the coronary heart disease prediction system includes a medical server and a multimodal data-based Coronary heart disease risk prediction device. In some embodiments, the medical server may establish a communication connection with a...
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The embodiment of the invention relates to the technical field of medical treatment, and discloses a coronary heart disease risk prediction method based on multi-modal data and related equipment. A processor of the equipment is used for executing the following steps: acquiring a cardiac ultrasonic report, waveform data and intervention data of each patient in a sample set before a first target moment; fusing the determined first representation vector of the cardiac ultrasonic report and the second representation vector of the waveform data to obtain a first target representation vector; inputting the first target representation vector and a second target representation vector of the intervention data into a specified classification model for training to obtain a coronary heart disease riskprediction model; and inputting the text data, the waveform data and the intervention data of the patient to be tested at the second target moment into the coronary heart disease risk prediction model to obtain a third moment and a third risk probability of suffering from the coronary heart disease and a fourth moment and a fourth risk probability of death of the patient to be tested, thereby improving the prediction effect of the coronary heart disease. The invention relates to a blockchain technology. The data can be stored in a blockchain.
Description
technical field [0001] The invention relates to the field of medical technology, in particular to a multimodal data-based coronary heart disease risk prediction method and related equipment. Background technique [0002] At present, coronary heart disease can be determined through cardiac ultrasound reports collected by heart monitoring equipment in a coronary heart disease care unit (Coronary Care Unit, CCU), wherein the coronary heart disease care unit is a care unit for monitoring coronary heart disease. At present, the risk of suffering from coronary heart disease or the risk of death of patients with coronary heart disease is determined mainly through the analysis of echocardiographic reports by medical staff. At present, there is also an intelligent prediction system for coronary heart disease. However, this system can only process a single type of data and a small amount of data. It is difficult to obtain good prediction results for large-scale multi-modal data. Ther...
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Login to View More IPC IPC(8): G16H50/30G16H50/20G06F16/35G06N3/04
CPCG16H50/30G16H50/20G06F16/353G06N3/045
Inventor 徐啸孙瑜尧徐衔刘小双
Owner PING AN TECH (SHENZHEN) CO LTD