請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73570完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳家麟 | |
| dc.contributor.author | Yun-Nien Huang | en |
| dc.contributor.author | 黃韻年 | zh_TW |
| dc.date.accessioned | 2021-06-17T08:06:11Z | - |
| dc.date.available | 2019-08-20 | |
| dc.date.copyright | 2019-08-20 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-19 | |
| dc.identifier.citation | [1] C Mathers, J Boerma, D. Fat, 'The global burden of disease: 2004 update' in , Geneva, Switzerland: Publications of the World Health Organization, 2008
[2] Statistics Ministry of Health and Welfare in Taiwan, 2018. Retrieved from https://dep.mohw.gov.tw/DOS/cp-1720-9734-113 [3] Kerri Smith, “Mental health: A world of depression A global view of the burden caused by depression.” 13 November 2014 Nature vol. 515,180–181 doi:10.1038/5151. [4] Albert Haque, Michelle Guo, Adam S Miner, Li Fei-Fei , ”Measuring Depression Symptom Severity from Spoken Language and 3D Facial Expressions” 2018. [5] American Psychiatric Association. (2000).” Diagnostic and statistical manual of mental disorders” (4th ed., text rev.).doi:10.1176/appi.books.9780890423349. [6] Kroenke K, Spitzer RL, Williams JB. “The PHQ-9: validity of a brief depression severity measure.” J Gen Intern Med. 2001;16(9):606–613. doi:10.1046/j.1525-1497.2001.016009606.x [7] A. P. Association et al. Diagnostic and statistical manual of mental disorders (DSM-5R ), 2013. [8] Ranna Parekh, M.D., M.P.H.” What Is Depression?” January 2017 https://www.psychiatry.org/patients-families/depression/what-is-depression. [9] Chia-Ming Chang M.D., Taiwan Anti-depression Association, 2008, Retrived 2019 , http://www.depression.org.tw/about/capter.asp. [10] Emily Anthes,“Mental health: There’s an app for that”, Nature News, 06 April 2016. [11] “What causes depression?” Harvard Health Publishing, Jun 2019 https://www.health.harvard.edu/mind-and-mood/what-causes-depression. [12] Wisniewski, S. R., Balasubramani, G. K., McCrone, P. & Brown, G. K. “Improving the Efficiency of Psychotherapy for Depression: Computer-Assisted Versus Standard CBT” Am. J. Psychiatry 175, 242–250 2018. doi.org/10.1176/appi.ajp.2017.17010089. [13] Cuijpers, P., Donker, T., Van Straten, A., Li, J., & Andersson, G. (2010). Is guided self-help as effective as face-to-face psychotherapy for depression and anxiety disorders? A systematic review and meta-analysis of comparative outcome studies. Psychological Medicine, 40(12), 1943-1957. doi:10.1017/S0033291710000772 [14] Fitzpatrick KK, Darcy A, Vierhile M. “Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial” MIR Ment. Health 2017 :e19 https://mental.jmir.org/2017/2/e19 DOI:10.2196/mental.7785. [15] Colin Barras, “Mental Health Apps Lean on Bots and Unlicensed”, Nature Medicine News 06 March 2019 [16] Kathleen Kara Fitzpatrick, PhD, Alison Darcy, PhD, and Molly Vierhile, BA, “Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial” JMIR Ment Health. 2017 Apr-Jun; 4(2): e19. Published online 2017 Jun 6. doi: 10.2196/mental.7785. [17] JILL, MORENCY LOUIS-PHILIPPE “REPORTING MENTAL HEALTH SYMPTOMS: BREAKING DOWN BARRIERS TO CARE WITH VIRTUAL HUMAN INTERVIEWERS” FRONTIERS IN ROBOTICS AND AI VOLUME 4 2017.HTTPS://WWW.FRONTIERSIN.ORG/ARTICLE/10.3389/FROBT.2017.00051. DOI=10.3389/FROBT.2017.00051. [18] Ries, E., “The lean startup: How today's entrepreneurs use continuous innovation to create radically successful businesses”,2011 [19] Apple Inc. Website. (2017). Apple App Store Policy Retrieved 2019 from Apple Inc. Website: https://www.apple.com/. [20] Alison Brunier, “Investing in treatment for depression and anxiety leads fourfold return”, WHO News, April 13 2016, HTTPS://WWW.WHO.INT/NEWS-ROOM/DETAIL/13-04-2016-INVESTING-IN-TREATMENT-FOR-DEPRESSION-AND-ANXIETY-LEADS-TO-FOURFOLD-RETURN. [22] National Collaborating Centre for Mental Health (UK). “Depression: The Treatment and Management of Depression in Adults (Updated Edition).”, NICE Clinical Guidelines, No. 90. Leicester (UK): British Psychological Society, 2010, https://www.ncbi.nlm.nih.gov/books/NBK63740/. [23] Per Carlbring, Gerhard Andersson.,“Successful Self-Treatment of a Case of Writer's Block.”, Cognitive Behaviour Therapy 40:1, pages 1-4, 2011. [24] Cuijpers, Pim; Donker, Tara; Weissman, Myrna M.; Ravitz, Paula; Cristea, Ioana A. (2016). 'Interpersonal Psychotherapy for Mental Health Problems: A Comprehensive Meta-Analysis'. American Journal of Psychiatry. 173 (7): 680–7. doi:10.1176/appi.ajp.2015.15091141. [25] O. M. Alabdani, A. A. Aldahash and L. Y. AlKhalil, 'A framework for depression dataset to build automatic diagnoses in clinically depressed Saudi patients,' 2016 SAI Computing Conference (SAI), London, 2016, pp. 1186-1189. doi: 10.1109/SAI.2016.7556128. [26] Ministry of Finance in Taiwan Website, Retrieved in 2019, Website: https://www.etax.nat.gov.tw/etwmain/web/ETW158W3. [27] Wikipedia of Value Proposition. Retrieved 2019, Last Modified in December 2016, Website: http://en.wikipedia.org/wiki/Value_proposition. [28] Osterwalder, A., Pigneur, Y., Bernarda, G., Smith, A. (2014) Value Proposition Design: How to Create Products and Services Customers Want, John Wiley & Sons. [29] Owler Inc. Website. Retrieved 2019 Website: https://www.owler.com/company/.[30] Depressy Trouble, “Depression is taking over the world-the shocking news.”, TVBS NEWS, June 2018, HTTPS://NEWS.TVBS.COM.TW/TTALK/DETAIL/LIFE/12976. [31] Jamie Lee, “Ad mod Income”, Retrieved 2019, https://www.jamleecute.com/app-mobile-ad-revenue-admob-行動廣告收入/. [32] Taiwan Counseling Psychologist Union(TCPU) , Retrieved 2019, http://www.tcpu.org.tw/front/bin/ptdetail.phtml?Part=certificate1080201&Category=453675. [33] Edouard Gaussen “Mapping out the Mental Health startup ecosystem” July 13, 2018 https://medium.com/venture-beyond/mapping-out-the-mental-health-startup-ecosystem-5cb4db031b54. [34] Allied Market Research, “Antidepressant Drugs Market by Depression Disorder, Product, and Geography: Global Opportunity Analysis and Industry Forecast, 2017-2023,' 2018 https://www.alliedmarketresearch.com/antidepressants-drugs-market [35] Abbot Laboratories, Global Depression Treatment Therapy Market Research and Forecast, 2018-2023, 2018, https://www.researchandmarkets.com/reports/3821008/global-depression-treatment- | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73570 | - |
| dc.description.abstract | Depression is a common but serious mental illness that affects the ability to think, and daily activities causing patients to suffer every day, and even committing suicide. From the statistics at World Health Organization, depression affected 350 million people worldwide, and WHO listed depression as the fourth most significant cause of suffering and disability worldwide [1]. Over 800,000 suicide every year, making it the second leading cause of death in 15-29 years old. In Taiwan alone, 2 million people had suffered from depression, and 1.27 million people now are taking long-term antidepressants by statistics of Taiwan Ministry of Health and Welfare [2]. Depression accounts for the biggest share of the world’s burden of disease, measured by years lost to disability (YLD): healthy years ‘lost’ because they are lived with a physical or mental disability. When ranked by disability and death combined, depression comes ninth behind prolific killers such as heart disease, stroke and HIV. Depression is caused by combination of genetics, biological, environment and psychological factors, and is treatable even for the most severe depression. Yet depression is widely undiagnosed and untreated because of social stigma, unawareness of the disease and lack of mental health resources [3]. To further explore the problems of insufficient of treatment of depression, we conduct interviews with depressed patients and therapists in Taiwan. From the interviews, we conclude that the reasons behind are high cost of mental treatment, low treatment availability, patients unaware of their depression severity level, and social stigma. Lack of assessment and awareness of depression result in insufficient and ineffective care for the disease despite the effective psychological and pharmacological treatments for depression. With the advance of 5G, the smartphones combined with cloud computing break through the limited computational power in smartphones. The raise of awareness of mental health in millennials results in prevalence of metal health APPs. We therefore propose a solution to diagnose depression with the help of facial recognition, speech processing, and natural language processing utilizing artificial intelligence. With the interface of mobile phone APP, our solution could easily access to everyone. This goal is to detect depression in the early stage to prevent further loss in financial and personal life, and urge our customers to go to professional clinics or hospitals for further help if diagnosed as severe or moderate depression. Automatic detection of depressive symptoms would potentially increase the rate of diagnostic visit, and patients’ awareness of their own depression severity levels, leading to faster intervention. In the research paper conducted by Professor Fei-Fei Li at Stanford University, automatic AI based depression severity test could achieve both accuracy and efficiency utilizing artificial intelligence [4]. The automatic detection algorithms identify facial traits and voices characteristics could help provide a universal and low-cost way of spotting the early signs of depression with smartphones. In practice, clinicians identify depression in patients by first measuring the severity of depressive symptoms during in-person clinical interviews. During these interviews, clinicians assess both verbal and non-verbal indicators of depressive symptoms including monotone pitch, reduced articulation rate, lower speaking volumes, fewer gestures, and more downward gazes [4]. If such symptoms persist for two weeks, the patient is considered to have a major or severe depressive episode. Structured questionnaires such as DSM-IV [5] and PHQ-9 [6] have been developed and validated in clinical populations to assess the severity of depressive symptoms.
The major purpose of our APP is to serve potential patients with convenient diagnosis to increase their self-awareness of their own depression severity levels in an accessible, affordable, and effective way. Also, the therapists and psychiatrists could use the App to monitor their patients and it serves as marketing channels for related fields such as hospitals, clinics, pharmaceutical companies, medical device companies, gaming, recreational, entertainment, and exercising App companies. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T08:06:11Z (GMT). No. of bitstreams: 1 ntu-108-R01749029-1.pdf: 3859249 bytes, checksum: d612c3745fa238baa20e6d52ca69bd8a (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | Table of Contents
ACKNOWLEDGEMENT I ABSTRACT II TABLE OF CONTENTS VI LIST OF FIGURES VIII LIST OF TABLES XI CHAPTER 1 INTRODUCTION 1 CHAPTER 2 LITERATURE REVIEW 7 2.1 CAUSES OF DEPRESSION 7 2.3 SEVERITY OF DEPRESSION 21 2.4 DEPRESSION TREATMENTS 25 2.5 VALUE PROPOSITION CANVAS 31 2.6. BUSINESS MODEL CANVAS 38 2.7 THE LEAN STARTUP 42 CHAPTER 3 VALUE PROPOSITION 47 3.1 INTERVIEWS 47 3.2 VALUE PROPOSITION CANVAS 58 CHAPTER 4 BUSINESS MODEL CANVAS 61 CHAPTER 5 OVERVIEW OF AI AND MENTAL HEALTH TECH STARTUPS TRENDS 65 5.1 OVERVIEW OF AI STARTUPS 65 5.2 OVERVIEW OF MENTAL HEALTH TECH STARTUPS 67 5.3 FUNDING FOR MENTAL HEALTH STARTUPS 71 5.4 CURRENT TRENDS OF DEPRESSION RELATED APPS 74 CHAPTER 6 MARKET ANALYSIS 79 6.1 GLOBAL ANTIDEPRESSANT DRUG MARKET 79 6.2 TAIWAN ANTIDEPRESSANT DRUG MARKET 87 6.3 GLOBAL DEPRESSION THERAPY MARKET 88 6.4 GLOBAL DEPRESSION DEVICE MARKET 90 CHAPTER 7 FINANCIAL PROJECTION 93 CHAPTER 8 IMPLEMENTATION PLAN 99 CHAPTER 9 RISK MANAGEMENT 105 CHAPTER 10 CONCLUSION 109 REFERENCE 111 APPENDIX: GANTT CHART 116 | |
| dc.language.iso | en | |
| dc.subject | 影像辨識 | zh_TW |
| dc.subject | 憂鬱症 | zh_TW |
| dc.subject | 人工智慧 | zh_TW |
| dc.subject | 語音處理 | zh_TW |
| dc.subject | Depression | en |
| dc.subject | Business Model Canvas | en |
| dc.subject | Value Proposition Model | en |
| dc.subject | 5G | en |
| dc.subject | Artificial Intelligence | en |
| dc.subject | Speech Recognition | en |
| dc.subject | Facial Recognition | en |
| dc.title | eTherapist自動化憂鬱症檢測應用程式 | zh_TW |
| dc.title | eTherapist – AI based automatic depression severity assessment APP | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 郭佳瑋,楊曙榮 | |
| dc.subject.keyword | 憂鬱症,影像辨識,語音處理,人工智慧, | zh_TW |
| dc.subject.keyword | Depression,Facial Recognition,Speech Recognition,Artificial Intelligence,5G,Value Proposition Model,Business Model Canvas, | en |
| dc.relation.page | 116 | |
| dc.identifier.doi | 10.6342/NTU201904048 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-08-20 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 企業管理碩士專班 | zh_TW |
| 顯示於系所單位: | 管理學院企業管理專班(Global MBA) | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-1.pdf 未授權公開取用 | 3.77 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
