BP neural network prediction model for suicide attempt among Chinese rural residents

• Published in: Journal of affective disorders Vol. 246; pp. 465 - 473
• Main Authors: Lyu, Juncheng, Zhang, Jie
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.03.2019
• Subjects: Adaptation, Psychological; Adolescent; Adult; Asian People - ethnology; Asian People - statistics & numerical data; BP neural network; Case-Control Studies; Child; China - epidemiology; Chinese rural residents; Crisis intervention; Depressive Disorder - diagnosis; Female; Humans; Impulsive Behavior; Logistic Models; Male; Middle Aged; Neural Networks, Computer; Prediction model; Psychiatric/Mental Health; Risk Factors; Rural Population - statistics & numerical data; Self Concept; Sensitivity and Specificity; Social Support; Suicide attempt; Suicide, Attempted - statistics & numerical data; Surveys and Questionnaires; Young Adult; China; Crisis intervention; BP neural network; Chinese rural residents; Prediction model; Suicide attempt
• ISSN: 0165-0327; 1573-2517; 1573-2517
• DOI: 10.1016/j.jad.2018.12.111

Highlight•The current study based spacious visual angle and provides a fire-new theoretical reference for searching the predictor of the attempted suicide. The current study handpicked 12 variables eventually, which greatly simplify the predictor system of the attempted suicide. •This study established the suicide attempt prediction model basing on BP neural network. Most previous literature established the prediction model by traditional prediction methods such as Logistic regression, which always ignored the application condition of the methods and always resulted in inaccurate results or larger prediction bias. The BP neural network, maximum simulates human brain intelligently, could deal with arbitrary nonlinear relation between variables. It has many incomparable advantages on complex model fitting and distribution approximation over the traditional statistical methods. The current study indicated that BP neural network improve the prediction accuracy compare with the traditional prediction. •The BP neural network established in current study has significance clinical meaning to distinguish suicide attempt for the clinical psychiatrist and lay theoretical foundation for artificial intelligence expert assisted diagnosis system for suicide attempt in the future.