Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening.

ABSTRACT:

Background

Patient registries and databases are essential tools for advancing clinical research in the area of rare diseases, as well as for enhancing patient care and healthcare planning. The primary aim of this study is a landscape analysis of available European data sources amenable to machine learning (ML) and their usability for Rare Diseases screening, in terms of findable, accessible, interoperable, reusable(FAIR), legal, and business considerations. Second, recommendations will be proposed to provide a better understanding of the health data ecosystem.

Methods

In the period of March 2022 to December 2022, a cross-sectional study using a semi-structured questionnaire was conducted among potential respondents, identified as main contact person of a health-related datab

SUBMITTER: Raycheva R 

PROVIDER: S-EPMC10998425 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature