Disease evaluation and illness risk assessment method and device

Abstract

The invention relates to the technical field of data processing, in particular to a disease evaluation and illness risk assessment method and device, a storage medium and an electronic terminal. The method comprises the steps of clustering medical data to conveniently obtain disease diagnosis and treatment data information of each patient; cleaning the disease diagnosis and treatment data information to obtain characteristic data of each disease in each time window; conducting similarity comparison processing on disease diagnosis data of an object to be assessed in the current time window andthe characteristic data of each disease in each time window to obtain assessment results of corresponding diseases and the probability estimation of the illness risk of the object to be assessed in the current time window. By means of the disease evaluation and illness risk assessment method and device, the conditions of diseases from which the object to be assessed surfers in a certain time period can be evaluated, and the illness risk that the object is likely to suffer from a disease can be estimated.

Description

technical field [0001] The present disclosure relates to the technical field of data processing, and in particular to a disease assessment and disease risk assessment method, a disease assessment and disease risk assessment device, a storage medium, and an electronic terminal. Background technique [0002] As people pay more attention to personal health and the advancement and deepening of medical informationization, disease prevention and risk assessment for individuals has become more and more important. For disease assessment and prevention, traditional medical research is based on randomized controlled trials, which have problems such as the lack of representativeness of the research subjects and the fact that the research endpoints cannot represent real clinical solutions. However, the existing disease prevention basically focuses on making judgments based on the subjective experience of doctors, lacking strong data support and quantitative analysis. [0003] Although ...

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Problems solved by technology

However, there are still many disadvantages in this solution, for example: (1) The population distribution is uneven; wearable devices are mainly concentrated in users aged 20 to 39 (data source: "Data Analysis Report on China's Smart Wearable Industry in the First Half of 2015") , the distribution of users tends to be healthy people, not widely representative; (2) Lack of authoritative data; wearable devices mainly collect users’ daily physiological indicators, but lack specific and key indicators of inspection and inspection data, and the model constructed based on this is not effective in convincing (3) Lack of professional judgment: wearable devices only collect physiological indicators for a period of time, and lack of professional judgment and index interpretation by doctors

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