Although mental disorders are one of the major disease burdens of Vietnamese people, up to now, early detection, monitoring of progress and evaluation of treatment effectiveness are still limited. Approaches to the clinical diagnosis of mental disorders are based on symptoms, physical disorders and tests reported by the patient, which in many situations, the pathological characteristics have not been accurately analyzed and determined. Currently popular structural imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI) are insufficient to identify underlying abnormalities that contribute to dysfunction, the cost of implementation is too high compared to the income of Vietnamese people, and it can only be done in central hospitals due to complex technical requirements. Diagnostic models based on artificial intelligence systems using fNIRS devices open up opportunities to diagnose mental disorders on a large scale, covering difficult areas (remote areas) and can be performed as part of a routine health check. On that basis, the goals of this project include (1) testing and calibrating the validity of the diagnostic model of some mental disorders in Vietnamese people based on comparative data using mobile fNIRS equipment with psychological tests and clinical diagnoses by specialists, (2) build a large database of behavioral and clinical indicators of mental health of Vietnamese people and (3) contributing to helping Vietnam become one of the countries with advanced methods and empirical data in Asia on predicting mental disorders. Longitudinal follow-up, periodic patient assessment, large-scale controlled study are conducted in Hanoi. The application of this research result will open up opportunities to conduct home-based, community-based exploration, screening, and treatment monitoring that can be expanded to disadvantaged areas, contributing to promoting health mentality of Vietnamese people.
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