MentalAId: an improved DenseNet model to assist scalable psychosis assessment.

ABSTRACT:

Background

The escalating mental health crisis during and post-COVID-19 underscores the urgent need for scalable, timely, cost-effective assessment solutions for general psychotic disorders. Regretfully, traditional symptom-based, one-to-one assessment face inherent limitations in large-scale and longitudinal screening, likely delaying early intervention.

Methods

We developed MentalAId, an improved densely connected convolutional network (DenseNet) model, to assist automated psychosis recognition, leveraging accessible routine laboratory data without requiring additional specialized tests. MentalAId learned subtle variations in 49 routine clinical hematological tests and two demographic variables (sex and age) across 28,746 individuals spanning four distinct cohorts: psychot

SUBMITTER: Li M 

PROVIDER: S-EPMC12312544 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature