Multi-Disease Prediction Based on Deep Learning: A Survey

作     者：Shuxuan Xie Zengchen Yu Zhihan Lv 

作者机构：College of Data Science Software EngineeringQingdao UniversityQingdao2660712China 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2021年第128卷第8期

页      面：489-522页

核心收录：

学科分类：0502[文学-外国语言文学] 050201[文学-英语语言文学] 05[文学] 

基　　金：This work was supported in part by the National Natural Science Foundation of China(Nos.61902203,61976242) Key Research and Development Plan-Major Scientific and Technological Innovation Projects of Shandong Province(2019JZZY020101) 

主　　题：Deep learning disease prediction Internet of Things COVID-19 precision medicine 

摘      要：In recent years, the development of artificial intelligence (AI) and the gradual beginning of AI’s research in themedical field have allowed people to see the excellent prospects of the integration of AI and healthcare. Amongthem, the hot deep learning field has shown greater potential in applications such as disease prediction and drugresponse prediction. From the initial logistic regression model to the machine learning model, and then to thedeep learning model today, the accuracy of medical disease prediction has been continuously improved, and theperformance in all aspects has also been significantly improved. This article introduces some basic deep learningframeworks and some common diseases, and summarizes the deep learning prediction methods correspondingto different diseases. Point out a series of problems in the current disease prediction, and make a prospect for thefuture development. It aims to clarify the effectiveness of deep learning in disease prediction, and demonstrates thehigh correlation between deep learning and the medical field in future development. The unique feature extractionmethods of deep learning methods can still play an important role in future medical research.