Disease assessment method, terminal device, and computer-readable medium

Abstract

The embodiment of the invention disclose a disease assessment method, a terminal device, and a computer readable medium, wherein the method includes: acquiring target sleep apnea data of a first unittime, the target sleep apnea data including sleep apnea data of a second unit time, the first unit time including the second unit time and being greater than the second unit time; using the target sleep apnea data as an input of a sleep apnea assessment model to obtain a sleep apnea assessment result, the sleep apnea assessment result being used for indicating whether a user corresponding to the target sleep apnea data has a sleep apnea during the second unit time. The disease assessment method can intelligently, accurately and quickly identify whether the user has a sleep apnea, and improvesthe accuracy and convenience of the disease assessment.

Description

technical field [0001] The present invention relates to the field of intelligent medical technology, in particular to a disease assessment method, a terminal device and a computer-readable medium. Background technique [0002] Sleep apnea syndrome (sleep apnea syndrome, SAS) is a symptom whose etiology and pathogenesis are not clear at present. Because apnea can cause recurrent hypercapnia and hypoxia at night, it can lead to complications such as coronary heart disease, diabetes, and cerebrovascular disease, and severe cases can even cause sudden death at night. How to accurately diagnose sleep apnea syndrome is an important part of night medicine. [0003] In order to solve the above problems, the SAS detection methods proposed in the prior art mainly include: X-ray projection detection, polysomnogram (Polysolnogram, PSG) detection, and nasopharyngeal fiberscope detection. However, it has been found in practice that the SAS detection methods provided by the prior art all...

AI Technical Summary

Problems solved by technology

However, it has been found in practice that the SAS detection methods provided by the prior art all rely on expensive medical equipment and are difficult to popularize

In particular, the PSG detection method needs to be tested for more than 7 hours in a sleep monitoring room equipped with expensive medical equipment, and there are many monitoring signals, and professional and technical personnel are required to make a diagnosis to analyze whether the user suffers from sleep apnea syndrome And the severity of the user's condition when suffering from sleep apnea syndrome, etc., which brings a lot of labor costs and equipment costs, and is not easy to popularize

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