A depression prediction model based on C4.5 decision tree

Xuan Zhang; Fei Wang

doi:10.1117/12.3011660

7 December 2023 A depression prediction model based on C4.5 decision tree

Xuan Zhang, Fei Wang

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294133 (2023) https://doi.org/10.1117/12.3011660
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

At present, there are many difficulties in the judgment of depression. Under the guidance of experts, this study selected a total of 26 depression features from four aspects: self-evaluation, psychological state, social support and physiological signs. Based on C4.5 decision tree algorithm, a depression prediction model was constructed. The experiment showed that the prediction accuracy was above 69%, which could play a role in the preliminary diagnosis of depression.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xuan Zhang and Fei Wang "A depression prediction model based on C4.5 decision tree", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294133 (7 December 2023); https://doi.org/10.1117/12.3011660

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