From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression-Reference-Cited by-同舟云学术

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From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression

Published:2024-03 Issue: Volume:158 Page:105541
ISSN:0149-7634
Container-title:Neuroscience & Biobehavioral Reviews
language:en
Short-container-title:Neuroscience & Biobehavioral Reviews

Author:

Leaning Imogen E.,Ikani Nessa,Savage Hannah S.,Leow Alex,Beckmann Christian,Ruhé Henricus G.,Marquand Andre F.

Funder

European Research Council

Dutch Research Council

Publisher

Elsevier BV

Reference41 articles.

1. Remote digital measurement of facial and vocal markers of major depressive disorder severity and treatment response: a pilot study;Abbas;Front. Digit. Health,2021

2. Adolescents' use of digital technologies and preferences for mobile health coaching in public mental health settings;Aschbrenner;Front. Public Health,2019

3. Tracking and monitoring mood stability of patients with major depressive disorder by machine learning models using passive digital data: Prospective naturalistic multicenter study;Bai;JMIR mHealth uHealth,2021

4. Systematic review of digital phenotyping and machine learning in psychosis spectrum illnesses;Benoit;Harv. Rev. Psychiatry,2020

5. Smartphone sensor data for identifying and monitoring symptoms of mood disorders: a longitudinal observational study;Braund;JMIR Ment. Health,2022

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Using Wearable Technology to Detect, Monitor, and Predict Major Depressive Disorder—A Scoping Review and Introductory Text for Clinical Professionals;Algorithms;2024-09-12

2. Digital biomarkers in depression: A systematic review and call for standardization and harmonization of feature engineering;Journal of Affective Disorders;2024-07

3. Predicting and Monitoring Symptoms in Diagnosed Depression Using Mobile Phone Data: An Observational Study;2024-06-17

4. Uncovering social states in healthy and clinical populations using digital phenotyping and Hidden Markov Models;2024-06-08

5. Closing the loop between environment, brain and mental health: how far we might go in real-life assessments?;Current Opinion in Psychiatry;2024-05-15

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