Infectious disease prediction method and system based on hidden Markov model, and medium

A prediction method and infectious disease technology, applied in the field of artificial intelligence smart medical care, can solve the problems of limited promotion and application, and the large difference between the predicted value and the actual situation, and achieve comprehensive data, improved analysis and processing capabilities, and strong forward-looking effects

Pending Publication Date: 2021-06-29
ACADEMY OF MILITARY MEDICAL SCI
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Problems solved by technology

At present, there are many mathematical models used in the research of infectious disease prediction. One type is a differential equation model based on dynamics. This model is suitable for infectious diseases in the natural development process. Under the effect of artificial prevention and control, the predicted value is very different from the actual situation. The first category is multiple regression analysis, arti

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  • Infectious disease prediction method and system based on hidden Markov model, and medium
  • Infectious disease prediction method and system based on hidden Markov model, and medium
  • Infectious disease prediction method and system based on hidden Markov model, and medium

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Embodiment 1

[0028] This embodiment discloses a method for predicting infectious diseases based on hidden Markov model, such as figure 1 shown, including the following steps:

[0029] S1 collects meteorological and hydrological information, and generates meteorological and hydrological observation sequences and infectious disease outbreak status sequences.

[0030] The m-year meteorological and hydrological observation sequence of an infectious disease O={V i |1≤i≤m}, where V i ={v it |1≤t≤12} represents the monthly meteorological and hydrological observation sequence over the years, and Meteorological and hydrological information includes: rainfall RF, average wind speed AW, average temperature AT, average maximum temperature HT, average minimum temperature LT, average pressure AP, average relative humidity ARH and sunshine hours SH eight types of meteorological and hydrological information vectors.

[0031] The infectious disease outbreak state sequence S={Q corresponding to the met...

Embodiment 2

[0050] Based on the same inventive concept, this embodiment discloses a hidden Markov model-based infectious disease prediction system, such as figure 2 shown, including:

[0051] The sequence acquisition module is used to collect meteorological and hydrological information, and generate meteorological and hydrological observation sequences and infectious disease outbreak status sequences;

[0052] The training sample generation module is used to preprocess the meteorological and hydrological observation sequence to generate a training sample set, and divide the samples in the training sample set into several sample feature intervals according to sample characteristics;

[0053] The matrix calculation module is used to calculate the observation probability matrix and the outbreak state transition probability matrix according to the sample characteristics, the sample characteristic interval and the infectious disease outbreak state sequence;

[0054] The model generation modu...

Embodiment 3

[0057] Based on the same inventive concept, this embodiment discloses a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to implement any of the above hidden Markov model-based Infectious Disease Prediction Methods.

[0058] Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

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Abstract

The invention relates to an infectious disease prediction method and system based on a hidden Markov model, and a medium. The method comprises the following steps: S1, generating a meteorological and hydrological observation sequence and an infectious disease outbreak state sequence; S2, preprocessing the meteorological and hydrological observation sequence to generate a training sample set, and dividing samples in the training sample set into a plurality of sample feature intervals according to sample features; S3, calculating an observation probability matrix and an outbreak state transition probability matrix according to the sample features, the sample feature intervals and the infectious disease outbreak state sequence; S4, generating a hidden Markov model according to the meteorological and hydrological observation sequence, the infectious disease outbreak state sequence, the observation probability matrix, the outbreak state transition probability matrix and the initial state probability distribution; and S5, predicting a meteorological and hydrological sequence at a certain moment in the future according to the historical meteorological and hydrological observation sequence, and substituting the predicted meteorological and hydrological sequence into the hidden Markov model to predict the infectious disease outbreak state. The method has the characteristics of high calculation speed, high accuracy and easy acquisition of sample data.

Description

technical field [0001] The invention relates to an infectious disease prediction method, system and medium based on a hidden Markov model, and belongs to the technical field of artificial intelligence and smart medical care. Background technique [0002] The outbreak of infectious diseases has had a certain impact on the stability of social order and human health. Based on the analysis of the epidemic law of infectious diseases, using scientific methods to predict the epidemic trend of infectious diseases can effectively prevent and control infectious diseases. Infectious disease prediction methods are mainly divided into qualitative prediction and quantitative prediction. In order to ensure the accuracy of the prediction results, it is necessary to choose reasonably according to the prediction purpose, epidemiological characteristics and data characteristics of the predicted infectious disease. Whether the incidence rate will increase or decrease in the future, you can cho...

Claims

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Application Information

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IPC IPC(8): G16H50/80
CPCG16H50/80
Inventor 方立群刘玮徐强陈津津蒋宝贵张海洋周士夏
Owner ACADEMY OF MILITARY MEDICAL SCI
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