A Review of the Main Factors, Computational Methods, and Databases Used in Depression Studies

Ariane C. B. da Silva, Renata C. Santana, Thiago H. N. de Lima, Maycoln L. M. Teodoro, Mark A. Song, Luis E. Zárate, Cristiane N. Nobre

2022

Abstract

Depression is a mental health disorder that affects millions of people worldwide. The disorder results from a complex interaction of biological, psychological, and social factors, leading to difficulty in both prognosis and diagnosis. In this work, we performed a review on studies about depression, to identify the main computational techniques used to support the prediction (prognosis and diagnosis) of depression, and the main attributes that might influence the development of the disorder. Our results indicate that, in the last ten years, Logistic Regression, Machine Learning techniques such as Support Vector Machines and Neural Networks, and other supervised learning algorithms, have been employed more frequently for studies predicting depression and selecting features related to it. Attributes like insomnia, gender, marital state, and use of tobacco, for example, were related to the development of depression. The review indicated growing effectiveness in using machine learning methods for analyzing data related to depression.

Paper Citation

in Harvard Style

B. da Silva A., Santana R., N. de Lima T., Teodoro M., Song M., Zárate L. and Nobre C. (2022). A Review of the Main Factors, Computational Methods, and Databases Used in Depression Studies. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF; ISBN 978-989-758-552-4, SciTePress, pages 413-420. DOI: 10.5220/0010815800003123

in Bibtex Style

@conference{healthinf22,
author={Ariane C. B. da Silva and Renata C. Santana and Thiago H. N. de Lima and Maycoln L. M. Teodoro and Mark A. Song and Luis E. Zárate and Cristiane N. Nobre},
title={A Review of the Main Factors, Computational Methods, and Databases Used in Depression Studies},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF},
year={2022},
pages={413-420},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010815800003123},
isbn={978-989-758-552-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF
TI - A Review of the Main Factors, Computational Methods, and Databases Used in Depression Studies
SN - 978-989-758-552-4
AU - B. da Silva A.
AU - Santana R.
AU - N. de Lima T.
AU - Teodoro M.
AU - Song M.
AU - Zárate L.
AU - Nobre C.
PY - 2022
SP - 413
EP - 420
DO - 10.5220/0010815800003123
PB - SciTePress