Online music-assisted rehabilitation system for depressed people based on deep learning
Tài liệu tham khảo
Balthazar, 2018, Protecting your patients' interests in the era of big data, artificial intelligence, and predictive analytics, J. Am. Coll. Radiol., 15, 580, 10.1016/j.jacr.2017.11.035
Cheng, 2017, Exploiting mobile big data: sources, features, and applications, IEEE Netw., 31, 72, 10.1109/MNET.2017.1500295NM
Deckro, 2021, Big data in the veterans health administration: a nursing informatics perspective, J. Nurs. Scholarsh., 53, 288, 10.1111/jnu.12631
Gonçalves-Pinho, 2021, Schizophrenia related hospitalizations–a big data analysis of a national hospitalization database, Psychiatry Q, 92, 239, 10.1007/s11126-020-09793-8
Gonçalves-Pinho, 2021, The use of big data in psychiatry–the role of pharmacy registries, Eur. Psychiatry, 64, S793, 10.1192/j.eurpsy.2021.2096
Gonçalves-Pinho, 2021, Schizophrenia hospitalizations-a big data approach, Eur. Psychiatry, 64, S157, 10.1192/j.eurpsy.2021.425
Graham, 2019, Artificial intelligence for mental health and mental illnesses: an overview, Curr. Psychiatry Rep., 21, 1, 10.1007/s11920-019-1094-0
Hong, 2020, Noise and the city: leveraging crowdsourced big data to examine the spatio-temporal relationship between urban development and noise annoyance, Environ. Plan. B: Urban Anal. City Sci., 47, 1201
Jung, 2021, Social mining-based clustering process for big-data integration, J. Ambient. Intell. Humaniz. Comput., 12, 589, 10.1007/s12652-020-02042-7
Liu, 2020, Bibliometric analysis on cardiovascular disease treated by traditional Chinese medicines based on big data, Int. J. Parallel Emerg. Distributed Syst., 35, 323, 10.1080/17445760.2019.1606912
Miller, 2020, Methamphetamine abuse trends in psychiatric emergency services: a retrospective analysis using big data, Community Ment. Health J., 56, 959, 10.1007/s10597-020-00563-1
Moessner, 2018, Analyzing big data in social media: text and network analyses of an eating disorder forum, Int. J. Eat. Disord., 51, 656, 10.1002/eat.22878
Nastro, 2021, Insideout project: using big data and machine learning for prevention in psychiatry, Eur. Psychiatry, 64, S343, 10.1192/j.eurpsy.2021.919
Park, 2017, Big data decision analysis of stress on adolescent mental health, J. Korea Soc. Comput. Inform., 22, 89
Perdue, 2018, Can big data predict the rise of novel drug abuse?, J. Drug Issues, 48, 508, 10.1177/0022042618772294
Popham, 2020, Constructing a public narrative of regulations for big data and analytics: results from a community-driven discussion, Soc. Sci. Comput. Rev., 38, 75, 10.1177/0894439318788619
Price, 2019, Privacy in the age of medical big data, Nat. Med., 25, 37, 10.1038/s41591-018-0272-7
Rudorfer, 2017, Psychopharmacology in the age of “big data”: the promises and limitations of electronic prescription records, CNS Drugs, 31, 417, 10.1007/s40263-017-0419-y
Shatte, 2019, Machine learning in mental health: a scoping review of methods and applications, Psychol. Med., 49, 1426, 10.1017/S0033291719000151
Stellbrink, 2017, Big data market analysis of e-health in medical neuroscience, Eur. Psychiatry, 41, S39, 10.1016/j.eurpsy.2017.01.178
Wang, 2018, An integrated big data analytics-enabled transformation model: application to health care, Inf. Manag., 55, 64, 10.1016/j.im.2017.04.001
Wilfling, 2020, Big data analysis techniques to address polypharmacy in patients–a scoping review, BMC Fam. Pract., 21, 1, 10.1186/s12875-020-01247-1