This paper is in the following e-collection/theme issue:

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1396) mHealth for Data Collection and Research (954) Wearable Devices and Sensors (887) Psychotic Disorders (160) Diagnostic Tools in Mental Health (242) Machine Learning (1460)

Published on in Vol 10, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31006, first published .
Predicting Psychotic Relapse in Schizophrenia With Mobile Sensor Data: Routine Cluster Analysis

Predicting Psychotic Relapse in Schizophrenia With Mobile Sensor Data: Routine Cluster Analysis

Predicting Psychotic Relapse in Schizophrenia With Mobile Sensor Data: Routine Cluster Analysis

Authors of this article:

Joanne Zhou1 Author Orcid Image ;   Bishal Lamichhane2 Author Orcid Image ;   Dror Ben-Zeev3 Author Orcid Image ;   Andrew Campbell4 Author Orcid Image ;   Akane Sano2 Author Orcid Image
Article Authors Cited by (15) Tweetations (10) Metrics

Journals

  1. Moukaddam N, Sano A, Salas R, Hammal Z, Sabharwal A. Turning data into better mental health: Past, present, and future. Frontiers in Digital Health 2022;4 View
  2. Lin S, Li P, Qin J, Liu Q, Zhang J, Meng N, Jia C, Zhu K, Lv D, Sun L, Shang T, Lin Y, Niu W, Wang T. Exploring the key factors of schizophrenia relapse by integrating LC-MS/1H NMR metabolomics and weighted correlation network analysis. Clinica Chimica Acta 2023;541:117252 View
  3. 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
  4. Zlatintsi A, Filntisis P, Garoufis C, Efthymiou N, Maragos P, Menychtas A, Maglogiannis I, Tsanakas P, Sounapoglou T, Kalisperakis E, Karantinos T, Lazaridi M, Garyfalli V, Mantas A, Mantonakis L, Smyrnis N. E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders Analyzing Long-Term Multimodal Data from Wearables and Video Captures. Sensors 2022;22(19):7544 View
  5. Yu H, Sun Y, Qin M, Ren J, Yu K, Song J, Zhou Y, Liu L. Perception of risk of relapse among patients with first episode and recurrent schizophrenia: a descriptive phenomenological study. BMC Psychiatry 2023;23(1) View
  6. Sharma G, Joshi A, Yadav D, Mohanty S. A Smart Healthcare Framework for Accurate Detection of Schizophrenia Using Multichannel EEG. IEEE Transactions on Instrumentation and Measurement 2023;72:1 View
  7. Lamichhane B, Zhou J, Sano A. Psychotic Relapse Prediction in Schizophrenia Patients Using A Personalized Mobile Sensing-Based Supervised Deep Learning Model. IEEE Journal of Biomedical and Health Informatics 2023;27(7):3246 View
  8. Gleeson J, McGuckian T, Fernandez D, Fraser M, Pepe A, Taskis R, Alvarez-Jimenez M, Farhall J, Gumley A. Systematic review of early warning signs of relapse and behavioural antecedents of symptom worsening in people living with schizophrenia spectrum disorders. Clinical Psychology Review 2024;107:102357 View
  9. Khoo L, Lim M, Chong C, McNaney R. Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches. Sensors 2024;24(2):348 View
  10. Zaher F, Diallo M, Achim A, Joober R, Roy M, Demers M, Subramanian P, Lavigne K, Lepage M, Gonzalez D, Zeljkovic I, Davis K, Mackinley M, Sabesan P, Lal S, Voppel A, Palaniyappan L. Speech markers to predict and prevent recurrent episodes of psychosis: A narrative overview and emerging opportunities. Schizophrenia Research 2024;266:205 View
  11. Guinart D, Fagiolini A, Fusar-Poli P, Giordano G, Leucht S, Moreno C, Correll C. On the Road to Individualizing Pharmacotherapy for Adolescents and Adults with Schizophrenia – Results from an Expert Consensus Following the Delphi Method. Neuropsychiatric Disease and Treatment 2024;Volume 20:1139 View
  12. Zlatintsi A, Filntisis P, Efthymiou N, Garoufis C, Retsinas G, Sounapoglou T, Maglogiannis I, Tsanakas P, Smyrnis N, Maragos P. Person Identification and Relapse Detection From Continuous Recordings of Biosignals Challenge: Overview and Results. IEEE Open Journal of Signal Processing 2024;5:641 View
  13. dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View