Nghiên cứu phát triển hệ chuyên gia mờ trong chẩn đoán rối loạn trầm cảm TT TIENG ANH

MINISTRY OF EDUCATION AND TRAINING MINISTRY OF NATIONAL DEFENCE ACADEMY OF MILITARY SCIENCE AND TECHNOLOGY MAI THI NU DEVELOPMENT RESEARCH ON FUZZY EXPERT SYSTEMS FOR THE DEPRESSIVE DISORDERS DIAGNOSIS Specialization: Mathematical Foundation for Informatic Code: 46 01 10 SUMMARY OF PhD THESIS IN MATHEMATICAL Ha Noi, 2021 This thesis has been completed at: ACADEMY OF MILITARY SCIENCE AND TECHNOLOGY MINISTRY OF NATIONAL DEFENCE Scientific Supervisor: Assoc Prof Dr Nguyen Hoang Phuong Dr Duong Tu Cuong Reviewer 1: Assoc Prof Dr Nguyen Tan An Reviewer 2: Assoc Prof Dr Nguyen Long Giang Reviewer 3: Dr Nguyen Manh Linh The thesis was defended at the Doctoral Evaluating Council at Academy level held at Academy of Military Science and Technology at … date ……., 2021 The thesis can be found at: - The Liblary of Academy of Military Science and Technology - Viet Nam National Liblary LIST OF SCIENTIFIC PUBLICATIONS Mai Thi Nu, Nguyen Hoang Phuong, K Hirota Modeling a Fuzzy Rule Based Expert System combining Positive and Negative Knowledge for Medical Consultations using the importance of Symptoms In Proc of IFSA-SCIS’2017, Otsu, Japan, June 27-30, 2017, Paper ID: #164 (Indexed in Scopus) Mai Thi Nu, Nguyen Hoang Phuong, Hoang Tien Dung STRESSDIAG: A Fuzzy Expert System for Diagnosis of Stress Types including Positive and Negative Rules, IFSA World Congress and NAFIPS Annunal Conference, June 18-22, 2019, USA, pp 371381, In Book: Fuzzy Techniques: Theory and Applications” Springer, 2019, volumn 1000 (Indexed in Scopus) Mai Thi Nu, Nguyen Hoang Phuong A Fuzzy Expert System based on positive rules for Depression Diagnoisis, Tạp chí Nghiên cứu khoa học công nghệ quân - Viện Khoa học Công nghệ quân sự, Số đặc san CNTT, 12/2020, pp 33-39 INTRODUCTION The necessary of the thesis According to the World Health Organization, "Depression" is a common mental disorder characterized by sadness, loss of interest, guilt or low selfesteem, disturbed sleep, or appetite, feeling tired and poor concentration It affects about 264 million people worldwide Especially when prolonged and in moderate or severe intensity, depression can become a serious health condition It can cause serious harm and ineffectiveness at work, school and home Most worryingly, depression can lead to suicide Depression is the fourth leading cause of death worldwide, the second leading cause of death among young people aged 15-29, projected to be the second leading cause of death by 2030 According to statistics of the Ministry of Health in 2017, in Vietnam, about 15% of the population suffer from common mental disorders related to depression, 50% of people suffer from serious depressive disorders Although they are many effective treatments for depression but the proportion of people in low-income and middle-income countries who not receive treatment for depressive disorder remains high There are many barriers to effective health care such as lack of resources, lack of medical professionals and social stigma Another barrier to effective health care is inaccurate diagnosis because the symptoms of a depressive disorder are difficult to assess and subjective, leading to inaccurate prescriptions Therefore, the treatment effect is not high Experienced team of doctors and equipment are two of the dilemmas in the battle with disease According to statistics of the Ministry of Health, the average rate is about 8-9 doctors / 10,000 people The percentage of doctors specializing in psychiatry is even less, psychiatrists are always in a serious shortage, while the majority of qualified doctors are concentrated at the central level Thus, it is necessary to exploit and use the knowledge of good specialists at the central level hospitals to train and share experience in examination and treatment of depression disorders for doctors who not have much experience, especially, for young medical doctors There are many methods to exploit and use knowledge, the expert system method is one potential approach to develop intelligent systems for disease disgnosis with high accuracy and high confidence to users Having many disease diagnostic support systems, the expert system method is the most appropriate approach, because the expert system method has a way of expressing knowledge by the production rules (IF… THEN…) This method has many advantages such as its syntactic closeness to the natural language descriptions of medical doctors, the expression is quite simple and intuitive, and can be deduced according to different strategies: progressive inference, backward inference, mixed inference (forward - backward), can check the inconsistency between rules, high modularity, that is, adding, removing, removing rules completely does not affect the other rules as well as the inference mechanism Usually, the diagnostic criteria according to the ICD-10 diagnostic criteria include clinical symptoms such as "hypochromia", "loss of interest" To diagnose depressive disorders, the symptom gets the values "yes" or "no" In the fact, the symptoms are fuzzy data, can be represented by fuzzy sets and get values in the range [0,1] Thus, in order to reduce the possibility of losing information and correct representation of disease symptoms, patient data should be represented by fuzzy sets Objectives of the research - Research on development a rule-based expert system for diagnosis of depressive disorder; - Building a positive rule base and a negative rule base for the experts system for depressive disorders diagnosis; - Helping medical doctors in the provinces and country sides, contributing to more accurate diagnosis, reducing waiting time, reducing overload for specialized hospitals, upper psychiatric departments Object and scope of the research - The research object of the thesis is depressive disorders, the expert system, the CADIAG-2 expert system - The research scope of the thesis topic is the fuzzy expert system based on the rules for depressive disorder diagnosis representation of positive knowledge, negative knowledge and inference mechanisms combining positive knowledge and negative knowledge for fuzzy expert system Content of the research - Research on the mental health care system in Vietnam, methods of depressive disorders diagnosis, symptoms and diagnostic procedures for depressive disorders; - Overview of research of fuzzy set theory, the expert system, the fuzzy expert system, the fuzzy expert system based on the rules, the CADIAG-2 expert system - Researching and developing the positive rules and negative rules for depressive disorders diagnosis; - Researching and proposing a model of an expert system based on the rule using positive rules for depressive disorder diagnosis - Researching and proposing a model of the expert system based on the rules combining positive rules and negative rules for depressive disorders diagnosis - Experimental implementation of the expert system with 264 depressive disorder patients - Evaluating the experimental results of the expert system, recommending the applications of the expert system in the diseases diagnosis Research method - Theoretical research method: theoretical research on methods of diagnosing depressive disorder, fuzzy set theory, expert system, CADIAG-2 expert system; - Experimental research method: collecting data on patients with depressive disorders; developing symptom-base, disease-base, and rule-base for expert systems; performing experiments on expert system software with collected data sets; evaluation of experimental results Structure of the thesis Apart from the introduction, the main contents of the thesis consists of three chapters: - Chapter presents some notions of depressive disorders and fuzzy expert systems, specifically the mental healthcare network in Vietnam, methods of diagnosing depressive disorders; fuzzy set theory, expert system, rule-based fuzzy expert system, CADIAG-2 expert system; Researching situation of development of diagnosing experts systems of depressive disorders in Vietnam and in the world, evaluation of limitations of studies about diagnostic systems of depressive disorders , and then proposing research directions of the thesis Through this chapter, the thesis shows an overview of the research problem of the thesis; - Chapter researches to propose a model of fuzzy expert system based on rule, using positive knowledge (positive rules for confirmation of conclusion) in diagnosing depressive disorders, this expert system is developed on CADIAG-2 expert system’s Max-Min approach; The contents presented include: knowledge base of expert system (symptom base, disease base, positive rules base); inference mechanism of the expert system; Experimental system with 264 cases of patients with depressive disorder; and analysis and evaluation of experimental results - Chapter presents the research and proposed model of fuzzy expert system based on the rules combining positive knowledge (positive rules) and negative knowledge (negative rules); expert system was developed, improved from fuzzy expert system based on the rules of using positive knowledge for diagnosing depressive disorder which was studied in chapter 2; presenting improvements of representing rules in knowledge base, improvement in the inference mechanism combining positive rules with negative rules; expert system testing with 264 cases of patients with depressive disorders; and analysis and evaluation of experimental results The conclusion part shows the research results of the thesis, the contribution of the thesis, the next research direction Finally, there are published works of the thesis Chapter Overview of depressive disorders and fuzzy expert systems 1.1 Overview of the depressive disorders diagnosis * Tests for depressive disorder - PHQ-9 consists of questions, PHQ-9 is designed to screen and help monitor the patient's response to treatment status Evaluating of depressive disorder by total score: ≤ total score ≤ is no depression; ≤ total score ≤ isrisk; 10 ≤ total score ≤ 14 is light depressive disorder; 15 ≤ total score ≤ 19 is middle depressive disorder; 20 ≤ total score ≤ 27 is serious depressive disorder - BECK includes 21 different indexes, BECK has been recognized by the World Health Organization for treatment Evaluating depressive disorder by total score, the total score