Exploring the Use of Machine Learning in Healthcare Prediction

Authors

  • Zhiyuan Ren

DOI:

https://doi.org/10.61173/jcxf9j51

Keywords:

Analyzing, Application, Machine learning

Abstract

The development process of modern society is accelerated, and at the same time, people’s need for medical care deepens. The main purpose of this study is to summarize the general situation of the current application of machine learning in medical prediction. This paper mainly analyzes the current situation of the application of machine learning models as well as the existence of problems by dissecting the current situation of the application of machine learning models and carries out a comprehensive analysis of its features. It focuses on analyzing the issues in the application of machine learning in disease prediction in imaging diagnosis, cancer risk assessment, cancer recurrence prediction, and mental illness prediction and make an arrangement summary about the current status of machine learning models in various healthcare prediction domains and owning characteristics The ultimate goal of this paper is to conclude the extent to which machine learning models can play a role in the context of the current continuous development of medical technology.

References

[1] Xing W, Xiaoyan L.Research on disease prediction model in Medical Big Data Environment[Jl. Manuf. Autom, 2022,44:24- 27.

[2] PEI Ying,WANG Shiqing,HAN Xiaosong. Disease trend prediction algorithm based on international news[J]. Advances in Biomedical Engineering,2023,44(04):398-404.

[3] HUANG Guoming,PENG Jie,ZHOU Kang,HUANG Tianming. Research on the application of big data analysis in preventive medicine[J]. Information and Computer (Theoretical Edition),2023,35(18):14-16.

[4] Lou Xiaofang. Research on the prediction model of breast cancer pathology information based on multiparameter magnetic resonance imaging histology [D]. Hangzhou University of Electronic Science and Technology: 2020.DOI: 10.27075/d.cnki. ghzdc.2020.000456.

[5] WANG Bo, YIN Shuai, DU Xiaoxin, ZHANG Jianfei, ZHOU Zhenyu. CircRNA-disease prediction based on graph neural network and random forest[J]. Journal of Higher Education Science,2024,44(02):36-41+47.

[6] XU He, ZHENG Qunli, XIE Zuoling, CHENG Haitao, LI Peng, JI Yimu. Interpretable deep learning model based on knowledge representation vectors and its application to disease prediction[J]. Data Acquisition and Processing,2023,38(04):777-791. DOI:10.16337/j.1004- 9037.2023.04.003.

[7] Huang Jian. Disease prediction in smart hospitals under big data technology[J]. China Science and Technology Information,2023(15):83-86.

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Published

2024-06-06