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ALEC2 - Adaptive Level of Effective and Continuous Care to common mental health disorders (CMDs)


This project combines expertise from Clinical Psychology and Computer Science to develop and implement ML methods to improve adherence, clinical efficiency and treatment efficacy in the delivery of (Braive’s) digital, iCBT supported psychotherapy solutions. Braive will bring to market a new patient-centric and R&D-driven solution that will address the shortcomings of current iCBT solutions. To meet this goal, we will create a new generation of iCBT that gradually automates the timely response to a patient’s development in treatment. Our new system - AVA, short for Automated Vigilance Assistant - will be able to: - Take patient’s guided inputs from clinically validated Mental Health Check (MHC) tool and support clinical decision-making by remote therapists, using quantitative scores and qualitative analysis; - Understand patients’ notes and queries through deep-learning and natural language understanding systems that; - Monitor and detect deviations from treatment trajectories, by interpreting written input and analyse sporadic queries with patients to assess compliance and do sentiment analysis; - Trigger human- or AI-led interventions targeted to each patient and to the observed deviation from treatment trajectory.

Project leader: Henrik Haaland Jahren

Started: 2021

Ends: 2025

Category: Næringsliv

Sector: Næringsliv

Budget: 13932000

Institution: BRAIVE AS

Address: Oslo