Current perspectives and challenges of using artificial intelligence in immunodeficiencies
Rivière, Jacques G. (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Cantenys Sabà, Roser (Servei Català de la Salut)
Carot-Sans, Gerard (Servei Català de la Salut)
Piera-Jiménez, Jordi (Servei Català de la Salut)
Butte, Manish J. (University of California)
Soler-Palacín, Pere (Hospital Universitari Vall d'Hebron)
Peng, Xiao P. (Montefiore Medical Center (Estats Units d'Amèrica))
Universitat Autònoma de Barcelona

Fecha:	2025
Resumen:	The rapid growth of artificial intelligence (AI) in health care is promising for screening and early diagnosis in settings that heavily rely on professional expertise, such as rare diseases like inborn errors of immunity (IEI). However, the development of AI algorithms for IEI and other rare diseases faces important challenges such as dataset sizes, availability and harmonization. Similarly, the implementation of AI-based strategies for screening and diagnosis of IEI in real-world scenarios is hampered by multiple factors including stakeholders' acceptance, ethical and legal constraints, and technologic barriers. Consequently, while the body of literature on AI-based solutions for early diagnosis of IEI continues to expand, clinical utility and widespread implementation remain limited. In this review, we provide an up-to-date comprehensive review of current applications and challenges facing AI use for IEI diagnosis and care.
Nota:	Altres ajuts: acords transformatius de la UAB
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article de revisió ; recerca ; Versió publicada
Materia:	Artificial intelligence ; Machine learning ; Inborn errors of immunity ; Primary immunodeficiency ; Secondary immunodeficiency ; Predictive modeling ; Genomics ; Electronic health records ; Clinical decision support ; Implementation science ; Screening algorithm
Publicado en:	The journal of allergy and clinical immunology, 2025 , ISSN 1097-6825

DOI: 10.1016/j.jaci.2025.06.015
PMID: 40588065

11 p, 2.1 MB

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