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AISN

Integrating AI in Stroke Neurorehabilitation
Funder: European CommissionProject code: 101057655 Call for proposal: HORIZON-HLTH-2021-DISEASE-04
Funded under: HE | HORIZON-RIA Overall Budget: 5,952,080 EURFunder Contribution: 5,940,890 EUR
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Description

Health services are increasingly moving towards a treatment continuum aligned with the patient journey. This transition will critically depend on the successful deployment of trustworthy AI-enhanced technologies that are accurate, secure, and trusted. The AISN project will develop and validate operating procedures and guidelines for integrating AI in a healthcare continuum, focussing on post-stroke rehabilitation. AISN delivers a representative AI health platform built from integrating validated platforms for data acquisition and access, clinical interpretation, whole-brain simulation, clinically validated intervention delivery and optimization and model-based prediction. The AISN integrated platform will be validated in the clinical context of rehabilitation in the outpatient and at-home phase and facilitate a concrete assessment of the fundamental ways in which AI-enhanced clinical decision-support will change the care pathway and the formulation of novel AI compatible treatment guidelines. AISN ensures an ethical approach by developing legal and ethical guidelines for the robust, fair, and trustworthy deployment of AI in health and validating acceptance and transparency of its solutions. Building on the AISN platform, the project will test current standard operating procedures for integrating AI in health care and formulate and validate new ones where needed. The AISN guidelines and procedures will emphasize the evidence base and safety of clinical interventions, transparency, prognostics at varying time-scales, personalization of interventions, access to disease-specific information by clinicians, patients and their carers, and assure that the potential of AI is fully developed in the service of value-based medicine satisfying standards of security and safety. We will go beyond currently available guidelines and frameworks by emphasizing explainability, AI tools with evolving performance, and the dynamic interaction between users and algorithms.

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