DeepO: an ontology-based deep learning system for disease prediction. (17th February 2022)

• Record Type: Journal Article
• Authors: Nguyen, Thi Phuong Trang; Nguyen, Ngan Luu-Thuy; Duong, Trong Hai
• Is Part Of: International journal of intelligent information and database systems. Volume 15:Number 2(2022)
• Page Start: 166
• Page End: 182
• Publication Date: 2022-02-17
• Subjects: disease prediction -- deep learning -- restricted Boltzmann machine -- formal concept analysis -- ontology; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Recently, there is a lot of research about building supporting diagnosis and treatment in medical care using deep learning. In this paper, we propose a method for building a deep learning model base on ontology structure for disease prediction (DeepO). The ontology structure will be automatically built based on the improvements of formal concepts analysis and pattern structure. We use deep restricted Boltzmann machine (DRBM) for the disease prediction task in DeepO. By using OCA in DeepO, our model learns more knowledge than RBM model. In experiments, we build a digestive disease diagnosis model with Vietnamese patient dataset.