Currently submitted to: Journal of Medical Internet Research
Date Submitted: Mar 13, 2026
Open Peer Review Period: Mar 16, 2026 - May 11, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Artificial Intelligence and Apps at the neuroscientist’s fingertips: NewPsy4u and the new frontier of digital psychiatry
ABSTRACT
Background:
The prevalence of mental health disorders is steadily increasing, while informative biomarkers remain lacking. Although artificial (AI) intelligence shows promise for revealing latent patterns in data, available datasets in the computational psychiatry community are still insufficient. Digital technologies and informatics tools could fill this gap, offering new strategies for collecting large real-world data. Furthermore, computational infrastructures provide scientists with access to e-services and powerful computational resources.
Objective:
We present the NewPsy4U web platform, which integrates data, AI pipelines, and mobile applications into an efficient environment from the end-user’s perspective.
Methods:
NewPsy4u is built on a LAMP architecture (Linux, Apache, MySQL, PHP) and is hosted at the IRCCS-FBF High Performance Computing (HPC) Center. These resources enable the execution of classical and generative AI algorithms required for computational psychiatry. The platform implements the highest standard protocols, while access is granted following registration and approval. The data repository complies with the FAIR principles (Findable, Accessible, Interoperable, Reusable), and the datasets provided are structured according to the OMOP Common Data Model or BIDS standard, enabling standardized data storage and interoperability. Mobile technology is integrated into NewPsy4u, allowing users to collect patient data using the experience sampling method (ESM). All mobile data are synchronized within the NewPsy4u web-based portal, where they can be managed for research purposes.
Results:
NewPsy4u is designed to provide access to pipelines and multiple datasets. The platform is freely accessible and its AI algorithms are released as open-source tools to promote transparency, reproducibility, and collaborative development. All AI algorithms available on the platform are offered as group or single-case second opinion tools. Multimodal patient records can be hosted in the web-platform with either open or restricted access. NewPsy4u currently includes data from 1900 patients diagnosed with various psychiatric conditions, collected at multiple time points. The platform architecture supports integration of multimodal data (sociodemographic, clinical, imaging and digital information captured by a mobile app) and serves as both a data-sharing solution and a hypothesis testing environment.
Conclusions:
NewPsy4u is a platform developed to support both research and clinical settings, offering an integrated suite of digital tools for psychiatry.
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