Title: DeepO: an ontology-based deep learning system for disease prediction

Authors: Thi Phuong Trang Nguyen; Ngan Luu-Thuy Nguyen; Trong Hai Duong

Addresses: Faculty of Information Technology, Ho Chi Minh City Open University, Vietnam ' University of Information Technology, Vietnam National University HCMC, Vietnam ' High Space Ltd, Ho Chi Minh, Vietnam

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.

Keywords: disease prediction; deep learning; restricted Boltzmann machine; formal concept analysis; ontology.

DOI: 10.1504/IJIIDS.2022.121897

International Journal of Intelligent Information and Database Systems, 2022 Vol.15 No.2, pp.166 - 182

Received: 21 Jul 2020
Accepted: 21 Feb 2021
Published online: 07 Apr 2022 *

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