정서행동질환의 진단과 치료에서 인공지능의 활용

키워드

참고문헌 (80)

1. "National mental health survey 2021"[URL]
2. Steel Z, "The global prevalence of common mental disorders : a systematic review and meta-analysis 1980-2013", Int J Epidemiol, 43, pp.476~493 (2014)
3. Ray A, "Artificial intelligence and psychiatry : an overview", Asian J Psychiatr, 70, pp.103021~ (2022)
4. Demyttenaere K, "Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys", JAMA, 291, pp.2581~2590 (2004)
5. Henderson C, "Mental health-related stigma in health care and mental health-care settings", Lancet Psychiatry, 1, pp.467~482 (2014)
6. Aiken RM, "Ethical guidelines for AI in education : starting a conversation", Int J Artif Intell Educ, 11, pp.163~176 (2000)
7. Turing AM, "The Essential Turing: the Ideas That Gave Birth to the Computer Age", pp.433~464 (2012)
8. McCarthy J, "Philosophical logic and artificial intelligence", pp.161~190 (1989), Springer
9. Kumar P, "Artificial intelligence(AI)-enabled CRM capability in healthcare : the impact on service innovation", Int J Inform Manag, 69, pp.102598~ (2023)
10. Bzdok D, "Machine learning for precision psychiatry : opportunities and challenges", Biol Psychiatry Cogn Neurosci Neuroimaging, 3, pp.223~230 (2018)
11. Schmidhuber J, "Deep learning in neural networks : an overview", Neural Netw, 61, pp.85~117 (2015)
12. Leondes CT, "Expert systems: the technology of knowledge management and decision making for the 21st century", pp.1~22 (2002), Academic Press
13. Hope BG, "An expert support system for service quality improvement", Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences, pp.183~190 (1994), IEEE
14. Azaab S, "A proposed expert system for selecting exploratory factor analysis procedures", J Coll Educ, 4, pp.9~26 (2000)
15. Hopfield JJ, "Neural networks and physical systems with emergent collective computational abilities", Proc Natl Acad Sci U S A, 79, pp.2554~2558 (1982)
16. Kaplan A, "Rulers of the world, unite! The challenges and opportunities of artificial intelligence", Bus Horiz, 63, pp.37~50 (2020)
17. Kelly CJ, "Key challenges for delivering clinical impact with artificial intelligence", BMC Med, 17, pp.195~ (2019)
18. Brinker TJ, "Comparing artificial intelligence algorithms to 157 German dermatologists : the melanoma classification benchmark", Eur J Cancer, 111, pp.30~37 (2019)
19. Hosny A, "Artificial intelligence in radiology", Nat Rev Cancer, 18, pp.500~510 (2018)
20. Vidal-Alaball J, "Artificial intelligence for the detection of diabetic retinopathy in primary care : protocol for algorithm development", JMIR Res Protoc, 8, pp.e12539~ (2019)
21. Afifi A, "Unsupervised detection of liver lesions in CT images", Annu Int Conf IEEE Eng Med Biol Soc, 2015, pp.2411~2414 (2015)
22. Chekroud AM, "The promise of machine learning in predicting treatment outcomes in psychiatry", World Psychiatry, 20, pp.154~170 (2021)
23. Koppe G, "Deep learning for small and big data in psychiatry", Neuropsychopharmacology, 46, pp.176~190 (2021)
24. Squarcina L, "Deep learning for the prediction of treatment response in depression", J Affect Disord, 281, pp.618~622 (2021)
25. Wiebe A, "Virtual reality in the diagnostic and therapy for mental disorders : a systematic review", Clin Psychol Rev, 98, pp.102213~ (2022)
26. Jiang F, "Artificial intelligence in healthcare : past, present and future", Stroke Vasc Neurol, 2, pp.230~243 (2017)
27. Allesøe RL, "Deep learning for cross-diagnostic prediction of mental disorder diagnosis and prognosis using Danish nationwide register and genetic data", JAMA Psychiatry, 80, pp.146~155 (2023)
28. Miller DD, "Artificial intelligence in medical practice : the question to the answer?", Am J Med, 131, pp.129~133 (2018)
29. Gabbard GO, "The early career psychiatrist and the psychotherapeutic identity", Acad Psychiatry, 41, pp.30~34 (2017)
30. Anderson HD, "Monitoring suicidal patients in primary care using electronic health records", J Am Board Fam Med, 28, pp.65~71 (2015)
31. Song DY, "The use of artificial intelligence in screening and diagnosis of autism spectrum disorder : a literature review", J Korean Acad Child Adolesc Psychiatry, 30, pp.145~152 (2019)
32. Shatte ABR, "Machine learning in mental health : a scoping review of methods and applications", Psychol Med, 49, pp.1426~1448 (2019)
33. Phan P, "Digital therapeutics in the clinic", Bioeng Transl Med, 8, pp.e10536~ (2023)
34. Salazar de Pablo G, "Implementing precision psychiatry : a systematic review of individualized prediction models for clinical practice", Schizophr Bull, 47, pp.284~297 (2021)
35. Gao S, "Machine learning in major depression : from classification to treatment outcome prediction", CNS Neurosci Ther, 24, pp.1037~1052 (2018)
36. Yeh SC, "A virtual-reality system integrated with neuro-behavior sensing for attention-deficit", hyperactivity disorder intelligent assessment, 2020, pp.28, 1899~1907
37. Goldman LS, "Diagnosis and treatment of attention-deficit", hyperactivity disorder in children and adolescents, 1998, pp.279, 1100~1107
38. Tenev A, "Machine learning approach for classification of ADHD adults", Int J Psychophysiol, 93, pp.162~166 (2014)
39. Loh HW, "Deep neural network technique for automated detection of ADHD and CD using ECG signal", Comput Methods Programs Biomed, 241, pp.107775~ (2023)
40. Chen T, "Diagnosing attention-deficit hyperactivity disorder(ADHD)using artificial intelligence : a clinical study in the UK", Front Psychiatry, 14, pp.1164433~ (2023)
41. Zhang-James Y, "Machine learning and MRI-based diagnostic models for ADHD : are we there yet?", J Atten Disord, 27, pp.335~353 (2023)
42. Baio J, "Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, United States, 2014", MMWR Surveill Summ, 67, pp.1~23 (2018)
43. Goldani AA, "Biomarkers in autism", Front Psychiatry, 5, pp.100~ (2014)
44. Yoo H, "Genetics of autism spectrum disorder : current status and possible clinical applications", Exp Neurobiol, 24, pp.257~272 (2015)
45. Zhou J, "Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk", Nat Genet, 51, pp.973~980 (2019)
46. Mahajan R, "Neuroimaging endophenotypes in autism spectrum disorder", CNS Spectr, 20, pp.412~426 (2015)
47. Falkmer T, "Diagnostic procedures in autism spectrum disorders : a systematic literature review", Eur Child Adolesc Psychiatry, 22, pp.329~340 (2013)
48. Duda M, "Use of machine learning for behavioral distinction of autism and ADHD", Transl Psychiatry, 6, pp.e732~ (2016)
49. Tariq Q, "Detecting developmental delay and autism through machine learning models using home videos of Bangladeshi children : development and validation study", J Med Internet Res, 21, pp.e13822~ (2019)
50. Liu W, "Identifying children with autism spectrum disorder based on their face processing abnormality : a machine learning framework", Autism Res, 9, pp.888~898 (2016)
51. Anzulewicz A, "Toward the autism motor signature : gesture patterns during smart tablet gameplay identify children with autism", Sci Rep, 6, pp.31107~ (2016)
52. Alcañiz Raya M, "Application of supervised machine learning for behavioral biomarkers of autism spectrum disorder based on electrodermal activity and virtual reality", Front Hum Neurosci, 14, pp.90~ (2020)
53. Kosmicki JA, "Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning", Transl Psychiatry, 5, pp.e514~ (2015)
54. Bussu G, "Prediction of autism at 3 years from behavioural and developmental measures in high-risk infants : a longitudinal cross-domain classifier analysis", J Autism Dev Disord, 48, pp.2418~2433 (2018)
55. Levy S, "Sparsifying machine learning models identify stable subsets of predictive features for behavioral detection of autism", Mol Autism, 8, pp.65~ (2017)
56. Wall DP, "Use of artificial intelligence to shorten the behavioral diagnosis of autism", PLoS One, 7, pp.e43855~ (2012)
57. Yu KH, "Artificial intelligence in healthcare", Nat Biomed Eng, 2, pp.719~731 (2018)
58. Saeedi A, "Major depressive disorder diagnosis based on effective connectivity in EEG signals : a convolutional neural network and long shortterm memory approach", Cogn Neurodyn, 15, pp.239~252 (2021)
59. Phang CR, "A multi-domain connectome convolutional neural network for identifying schizophrenia from EEG connectivity patterns", IEEE J Biomed Health Inform, 24, pp.1333~1343 (2020)
60. Elvevåg B, "Quantifying incoherence in speech : an automated methodology and novel application to schizophrenia", Schizophr Res, 93, pp.304~316 (2007)
61. Shuren J, "Digital therapeutics for MCI and Alzheimer’s disease : a regulatory perspective-highlights from the clinical trials on Alzheimer’s disease conference(CTAD)", J Prev Alzheimers Dis, 9, pp.236~240 (2022)
62. Wood LJ, "Developing Kaspar : a humanoid robot for children with autism", Int J Soc Robot, 13, pp.491~508 (2021)
63. Pennisi P, "Autism and social robotics : a systematic review", Autism Res, 9, pp.165~183 (2016)
64. Huijnen CAGJ, "Roles, strengths and challenges of using robots in interventions for children with autism spectrum disorder(ASD)", J Autism Dev Disord, 49, pp.11~21 (2019)
65. Kollins SH, "Effectiveness of a digital therapeutic as adjunct to treatment with medication in pediatric ADHD", NPJ Digit Med, 4, pp.58~ (2021)
66. Masi L, "Video games in ADHD and non-ADHD children : modalities of use and association with ADHD symptoms", Front Pediatr, 9, pp.632272~ (2021)
67. Sujar A, "Attention deficit hyperactivity disorder assessment based on patient behavior exhibited in a car video game : a pilot study", Brain Sci, 12, pp.877~ (2022)
68. Simon L, "Comparative efficacy of onsite, digital, and other settings for cognitive behavioral therapy for insomnia : a systematic review and network meta-analysis", Sci Rep, 13, pp.1929~ (2023)
69. Choi HJ, "Digital therapeutics reimbursement system in Germany and its implications", HIRA Res, 2, pp.24~35 (2022)
70. Cho CH, "Clinical application of digital therapeutics for insomnia", Sleep Med Psychophysiol, 28, pp.6~12 (2021)
71. Park KM, "Can digital therapeutics open a new era of sleep medicine?", Chronobiol Med, 3, pp.142~148 (2021)
72. Dequanter S, "The effectiveness of e-Health solutions for aging with cognitive impairment : a systematic review", Gerontologist, 61, pp.e373~e394 (2021)
73. Fitzpatrick KK, "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, 4, pp.e19~ (2017)
74. Kaplan A, "Evaluating the impact of Freespira on panic disorder patients’ health outcomes and healthcare costs within the allegheny health network", Appl Psychophysiol Biofeedback, 45, pp.175~181 (2020)
75. Christensen DR, "Adding an internet-delivered treatment to an efficacious treatment package for opioid dependence", J Consult Clin Psychol, 82, pp.964~972 (2014)
76. Bain EE, "Use of a novel artificial intelligence platform on mobile devices to assess dosing compliance in a phase 2 clinical trial in subjects with schizophrenia", JMIR Mhealth Uhealth, 5, pp.e18~ (2017)
77. du Sert OP, "Virtual reality therapy for refractory auditory verbal hallucinations in schizophrenia : a pilot clinical trial", Schizophr Res, 197, pp.176~181 (2018)
78. Doraiswamy PM, "Artificial intelligence and the future of psychiatry : insights from a global physician survey", Artif Intell Med, 102, pp.101753~ (2020)
79. Bourla A, "Psychiatrists’ attitudes toward disruptive new technologies : mixed-methods study", JMIR Ment Health, 5, pp.e10240~ (2018)
80. "Digital therapeutics & wellness: market forecasts, key trends & business models 2022-2026"[URL]