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Machine Learning-Based Discrimination of Unipolar Depression and Bipolar Disorder With Streamlined Shortlist in Adolescents of Different Ages by duymanhs2lc is a document available to read on EtoBox.

What is Machine Learning-Based Discrimination of Unipolar Depression and Bipolar Disorder With Streamlined Shortlist in Adolescents of Different Ages about?

This study investigates the use of machine learning to differentiate between unipolar depression (UD) and bipolar disorder (BD) in adolescents aged 12-18, addressing the challenges posed by overlapping symptoms. A total of 1587 UD and 246 BD adolescents were analyzed using various machine learning algorithms, with the Random Forest algorithm achieving the highest accuracy (AUC 0.88-0.90) and a 25-item shortlist developed for efficient diagnosis. The findings suggest that this method can provide a rapid and

Author

duymanhs2lc

Language

EN