Progress in biomedical data analysis based on deep learning.
10.7507/1001-5515.201907016
- Author:
Suyi LI
1
;
Shijie TANG
1
;
Feng LI
1
;
Jianzhuo QI
2
;
Wenji XIONG
3
Author Information
1. College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, P.R.China.
2. Xining No.1 People's Hospital, Xining 810000, P.R.China.
3. The First Hospital of Jilin University, Changchun 130021, P.R.China.
- Publication Type:Journal Article
- Keywords:
biomedical science;
data analysis;
deep learning
- MeSH:
Algorithms;
Biomedical Technology;
Data Analysis;
Deep Learning
- From:
Journal of Biomedical Engineering
2020;37(2):349-357
- CountryChina
- Language:Chinese
-
Abstract:
Traditional biomedical data analysis technology faces enormous challenges in the context of the big data era. The application of deep learning technology in the field of biomedical analysis has ushered in tremendous development opportunities. In this paper, we reviewed the latest research progress of deep learning in the field of biomedical data analysis. Firstly, we introduced the deep learning method and its common framework. Then, focusing on the proposal of biomedical problems, data preprocessing method, model building method and training algorithm, we summarized the specific application of deep learning in biomedical data analysis in the past five years according to the chronological order, and emphasized the application of deep learning in medical assistant diagnosis. Finally, we gave the possible development direction of deep learning in the field of biomedical data analysis in the future.
