Published on in Vol 24 , No 2 (2022) :February
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/28735, first published
.

Journals
- De La Fabián R, Jiménez-Molina Á, Pizarro Obaid F. A critical analysis of digital phenotyping and the neuro-digital complex in psychiatry. Big Data & Society 2023;10(1):205395172211490 View
- Dlima S, Shevade S, Menezes S, Ganju A. Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR Bioinformatics and Biotechnology 2022;3(1):e39618 View
- Diniz E, Fontenele J, de Oliveira A, Bastos V, Teixeira S, Rabêlo R, Calçada D, dos Santos R, de Oliveira A, Teles A. Boamente: A Natural Language Processing-Based Digital Phenotyping Tool for Smart Monitoring of Suicidal Ideation. Healthcare 2022;10(4):698 View
- Choudhary S, Thomas N, Alshamrani S, Srinivasan G, Ellenberger J, Nawaz U, Cohen R. A Machine Learning Approach for Continuous Mining of Nonidentifiable Smartphone Data to Create a Novel Digital Biomarker Detecting Generalized Anxiety Disorder: Prospective Cohort Study. JMIR Medical Informatics 2022;10(8):e38943 View
- Elmer T, Lodder G. Modeling social interaction dynamics measured with smartphone sensors: An ambulatory assessment study on social interactions and loneliness. Journal of Social and Personal Relationships 2023;40(2):654 View
- de Oliveira A, Diniz E, Teixeira S, Teles A. How can machine learning identify suicidal ideation from user's texts? Towards the explanation of the Boamente system. Procedia Computer Science 2022;206:141 View
- Moura I, Teles A, Viana D, Marques J, Coutinho L, Silva F. Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review. Journal of Biomedical Informatics 2023;138:104278 View
- Chen Z, Kulkarni P, Galatzer-Levy I, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. Patterns 2022;3(11):100602 View
- Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 2022;22(10):3893 View
- Bavaresco R, Barbosa J. Ubiquitous computing in light of human phenotypes: foundations, challenges, and opportunities. Journal of Ambient Intelligence and Humanized Computing 2023;14(3):2341 View
- Schmidt S, D'Alfonso S. Clinician perspectives on how digital phenotyping can inform client treatment. Acta Psychologica 2023;235:103886 View
- Ford T, Buchanan D, Azeez A, Benrimoh D, Kaloiani I, Bandeira I, Hunegnaw S, Lan L, Gholmieh M, Buch V, Williams N. Taking modern psychiatry into the metaverse: Integrating augmented, virtual, and mixed reality technologies into psychiatric care. Frontiers in Digital Health 2023;5 View
- Jabir A, Martinengo L, Lin X, Torous J, Subramaniam M, Tudor Car L. Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments. Journal of Medical Internet Research 2023;25:e44548 View
- Yeo G, Loo G, Oon M, Pang R, Ho D. A Digital Peer Support Platform to Translate Online Peer Support for Emerging Adult Mental Well-being: Randomized Controlled Trial. JMIR Mental Health 2023;10:e43956 View
- Galatzer-Levy I, Onnela J. Machine Learning and the Digital Measurement of Psychological Health. Annual Review of Clinical Psychology 2023;19(1):133 View
Books/Policy Documents
- Marchionatti L, Mastella N, Bouvier V, Passos I. Digital Mental Health. View