D4.2 / The AI-PROGNOSIS digital health ecosystem (Alpha version)

The goal of Deliverable 4.2, 'The AI-PROGNOSIS Digital Health Ecosystem (Alpha Version),' is to serve as a companion report detailing the development of the AI-PROGNOSIS digital health ecosystem applications (mAI-Health, mAI-Care, and mAI-Insights). It highlights the progress from initial user requirements gathering through co-creation workshops to deploying functional alpha-version prototypes. These applications serve different user groups, including individuals at risk of developing Parkinson’s Disease, patients, and healthcare professionals. Built as part of the ecosystem's Minimum Viable Products (MVPs), they incorporate advanced data collection and processing mechanisms, such as smartwatch integration, a custom virtual keyboard, and active digital cognitive function tests. The development strategy emphasises containerised deployment, continuous integration, and robust system performance. Key components include the Ingest Application Programming Interface (API), which securely aggregates diverse health data, and the artificial intelligence (AI) Models API, which provides predictive insights. Deployment leverages Kubernetes for scalability, Argo CD for GitOps-based configuration management and monitoring stack, including Prometheus and Grafana, for performance measurement. The system prioritises data security and resilience, integrating real-time alerts and automated backups to ensure reliability.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-29
DOI
https://doi.org/10.5281/zenodo.15542532
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

D4.2 / The AI-PROGNOSIS digital health ecosystem (Alpha version)

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

D4.2 / The AI-PROGNOSIS digital health ecosystem (Alpha version)

article en

Abstract

The goal of Deliverable 4.2, 'The AI-PROGNOSIS Digital Health Ecosystem (Alpha Version),' is to serve as a companion report detailing the development of the AI-PROGNOSIS digital health ecosystem applications (mAI-Health, mAI-Care, and mAI-Insights). It highlights the progress from initial user requirements gathering through co-creation workshops to deploying functional alpha-version prototypes. These applications serve different user groups, including individuals at risk of developing Parkinson’s Disease, patients, and healthcare professionals. Built as part of the ecosystem's Minimum Viable Products (MVPs), they incorporate advanced data collection and processing mechanisms, such as smartwatch integration, a custom virtual keyboard, and active digital cognitive function tests. The development strategy emphasises containerised deployment, continuous integration, and robust system performance. Key components include the Ingest Application Programming Interface (API), which securely aggregates diverse health data, and the artificial intelligence (AI) Models API, which provides predictive insights. Deployment leverages Kubernetes for scalability, Argo CD for GitOps-based configuration management and monitoring stack, including Prometheus and Grafana, for performance measurement. The system prioritises data security and resilience, integrating real-time alerts and automated backups to ensure reliability.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 62%
Artificial Intelligence in Healthcare and Education
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