Predicting quetiapine dose in patients with depression using machine learning techniques based on real-world evidence.

ABSTRACT:

Background

Being one of the most widespread, pervasive, and troublesome illnesses in the world, depression causes dysfunction in various spheres of individual and social life. Regrettably, despite obtaining evidence-based antidepressant medication, up to 70% of people are going to continue to experience troublesome symptoms. Quetiapine, as one of the most commonly prescribed antipsychotic medication worldwide, has been reported as an effective augmentation strategy to antidepressants. The right quetiapine dose and personalized quetiapine treatment are frequently challenging for clinicians. This study aimed to identify important influencing variables for quetiapine dose by maximizing the use of data from real world, and develop a predictive model of quetiapine dose through machine l

SUBMITTER: Hao Y 

PROVIDER: S-EPMC10771703 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature