Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study

Abigail Ortiz; Arend Hintze; Rachael Burnett; Christina Gonzalez-Torres; Samantha Unger; Dandan Yang; Jingshan Miao; Martin Alda; Benoit H. Mulsant

doi:10.1186/s12888-022-03923-1

Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study

Abigail Ortiz, Arend Hintze, Rachael Burnett, Christina Gonzalez-Torres, Samantha Unger, Dandan Yang, Jingshan Miao, Martin Alda, Benoit H. Mulsant

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Original language	English
Article number	288
Journal	BMC Psychiatry
Volume	22
Issue number	1
DOIs	https://doi.org/10.1186/s12888-022-03923-1
Publication status	Published - Dec 2022
Externally published	Yes

ASJC Scopus Subject Areas

Psychiatry and Mental health

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1186/s12888-022-03923-1

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Ortiz, A., Hintze, A., Burnett, R., Gonzalez-Torres, C., Unger, S., Yang, D., Miao, J., Alda, M., & Mulsant, B. H. (2022). Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study. BMC Psychiatry, 22(1), Article 288. https://doi.org/10.1186/s12888-022-03923-1

Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study. / Ortiz, Abigail; Hintze, Arend; Burnett, Rachael et al.
In: BMC Psychiatry, Vol. 22, No. 1, 288, 12.2022.

Research output: Contribution to journal › Article › peer-review

Ortiz, A, Hintze, A, Burnett, R, Gonzalez-Torres, C, Unger, S, Yang, D, Miao, J, Alda, M & Mulsant, BH 2022, 'Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study', BMC Psychiatry, vol. 22, no. 1, 288. https://doi.org/10.1186/s12888-022-03923-1

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author = "Abigail Ortiz and Arend Hintze and Rachael Burnett and Christina Gonzalez-Torres and Samantha Unger and Dandan Yang and Jingshan Miao and Martin Alda and Mulsant, {Benoit H.}",

note = "Funding Information: This work has been supported by the National Institute of Mental Health (NIMH) grant 1R21MH123849-01A1 (Principal Investigator: Dr. Ortiz) and by the Canadian Institutes of Health Research (CIHR) grant 02010PJT-450770-BSB-CEAH-188794 (Principal Investigator: Dr. Ortiz). Funding agencies had no role in the design and conduct of the study. The research team had full autonomy in all aspects of the study. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

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AU - Yang, Dandan

AU - Miao, Jingshan

AU - Alda, Martin

AU - Mulsant, Benoit H.

N1 - Funding Information: This work has been supported by the National Institute of Mental Health (NIMH) grant 1R21MH123849-01A1 (Principal Investigator: Dr. Ortiz) and by the Canadian Institutes of Health Research (CIHR) grant 02010PJT-450770-BSB-CEAH-188794 (Principal Investigator: Dr. Ortiz). Funding agencies had no role in the design and conduct of the study. The research team had full autonomy in all aspects of the study. Publisher Copyright: © 2022, The Author(s).

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Identifying patient-specific behaviors to understand illness trajectories and predict relapses in bipolar disorder using passive sensing and deep anomaly detection: protocol for a contactless cohort study

ASJC Scopus Subject Areas

UN SDGs

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