Prediction of depressive symptoms onset and long-term trajectories in home-based older adults using machine learning techniques-Reference-Cited by-同舟云学术

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Prediction of depressive symptoms onset and long-term trajectories in home-based older adults using machine learning techniques

Published:2022-02-04 Issue:1 Volume:27 Page:8-17
ISSN:1360-7863
Container-title:Aging & Mental Health
language:en
Short-container-title:Aging & Mental Health

Author:

Lin Shaowu¹²³,Wu Yafei¹²³^ORCID,He Lingxiao¹³,Fang Ya¹²³

Affiliation:

1. The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China

2. National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China

3. Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, Xiamen, China

Funder

National Natural Science Foundation of China

Field Investigation Foundation of Xiamen University

Publisher

Informa UK Limited

Subject

Psychiatry and Mental health,Geriatrics and Gerontology,Gerontology,Pshychiatric Mental Health

Link

https://www.tandfonline.com/doi/pdf/10.1080/13607863.2022.2031868

Reference70 articles.

1. Twelve-year depressive symptom trajectories and their predictors in a community sample of older adults

2. Automated Depression Detection Using Deep Representation and Sequence Learning with EEG Signals

3. What Are the Causes of Late-Life Depression?

4. Trajectory and Socioeconomic Predictors of Depression in a Prospective Study of Residents of New York City

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3. Long-term trajectories of depressive symptoms in deployed military personnel: A 10-year prospective study;Journal of Affective Disorders;2024-06

4. Impact of Artificial Intelligence in Nursing for Geriatric Clinical Care for Chronic Diseases: A Systematic Literature Review;IEEE Access;2024

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