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學術出版;;Publications

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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Subject: search.filters.subject.Depression diagnosis

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    Item type:Item,
    A Mental Disorder Early Warning Approach by Observing Depression Symptom in Social Diary
    (2014)
    Fang, Ying-En
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    Tai, Chih-Hua
    ;
    Chang, Yue-Shan
    ;
    Fan, Chih-Tien
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    資訊工程學系
    With the advances of information technology, there are increasing researches aiming at assisting depression diagnosis and treatment. In most of them the user is necessarily actively joining the diagnosis and treatment program while he has perceived mental disorder himself. In order to early prevent the mental disorder, in this paper we propose an early warning mechanism that observes and mines user diary published on social network platform, and generates a score of getting mental disordered or depressed. If the score is large than a threshold, the system can notify the user and his friends on the social network to take care about the friend. We have conducted experiments to evaluate the proposed approach, and the results show that the proposed approach is effective.
  • Thumbnail Image
    Item type:Item,
    Mobile cloud-based depression diagnosis using an ontology and a Bayesian network
    (2015-02-01)
    Chang, Yue-Shan
    ;
    Fan, Chih-Tien
    ;
    Lo, Win-Tsung
    ;
    Hung, Wan-Chun
    ;
    Yuan, Shyan-Ming
    Recently, depression has becomes a widespread disease throughout the world. However, most people are not aware of the possibility of becoming depressed during their daily lives. Therefore, obtaining an accurate diagnosis of depression is an important issue in healthcare. In this study, we built an inference model based on an ontology and a Bayesian network to infer the possibility of becoming depressed, and we implemented a prototype using a mobile agent platform as a proof-of-concept in the mobile cloud. We developed an ontology model based on the terminology used to describe depression and we utilized a Bayesian network to infer the probability of becoming depressed. We also implemented the system using multi-agents to run on the Android platform, thereby demonstrating the feasibility of this method, and we addressed various implementation issues. The results showed that our method may be useful for inferring a diagnosis of depression. (C) 2014 Elsevier B.V. All rights reserved.