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“Code of ethical practice” for sharing and access to personal data for AI-/ ML-based technologies in rare diseases genetic NBS research project: a collaborative construction in a European IMI project
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Centre for Research Ethics and Bioethics.ORCID iD: 0000-0002-3706-7669
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2025 (English)In: AI and Ethics, ISSN 2730-5953, E-ISSN 2730-5961Article in journal (Refereed) Epub ahead of print
Abstract [en]

The early diagnosis of rare diseases (RDs) is crucial for timely intervention and effective management. The Screen4Care project seeks to accelerate this process by combining newborn screening with artificial intelligence (AI) and machine-learning (ML) tools. The Screen4Care interdisciplinary approach aims to reduce the lengthy diagnostic journey for individuals with RDs and improve their quality of life. A Code of Ethical Practice (CoEP) was developed to ensure the ethical handling of personal data in AI/ML-based screening. This CoEP outlines standards for how Screen4Care partner organizations can share and access patient data while minimizing the risk of misuse. Developed through the combined efforts of expert groups, European teams, advisory bodies, and patient organizations, the CoEP ensures a secure framework for data handling. This establishes a robust set of ethical principles, ensuring that data collection and sharing are conducted in a safe and responsible manner. This framework supports innovative AI/ML solutions, optimizing the diagnosis, treatment, and management of RDs, while safeguarding the interests of individuals and their families.

Place, publisher, year, edition, pages
Springer, 2025.
Keywords [en]
Code of ethical practice, Genetic newborn screening, Artificial intelligence, Machine learning, Rare diseases
National Category
Computer and Information Sciences Ethics
Identifiers
URN: urn:nbn:se:uu:diva-555099DOI: 10.1007/s43681-025-00727-3OAI: oai:DiVA.org:uu-555099DiVA, id: diva2:1953749
Available from: 2025-04-23 Created: 2025-04-23 Last updated: 2025-04-23Bibliographically approved

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