Proceedings of the second Artificial Intelligence in Primary Immunodeficiency (AIPI) meeting
Rivière, Jacques G. (Universitat Autònoma de Barcelona. Departament de Pediatria, Obstetrícia i Ginecologia i de Medicina Preventiva i Salut Pública)
Bastarache, Lisa (Vanderbilt University Medical Center)
Campos, Luiza C. (University College London Institute of Immunity and Transplantation)
Carot-Sans, Gerard (Servei Català de la Salut)
Chin, Aaron (University of California. Department of Pediatrics)
Chunara, Rumi (New York University)
Cunningham-Rundles, Charlotte (Icahn School of Medicine at Mount Sinai (Nova York, Estats Units d'Amèrica))
Erra, Lorenzo (Instituto de Biociencias, Biotecnología y Biología Traslacional (Argentina))
Farmer, Jocelyn (Beth Israel Lahey Health (Estats Units d'Amèrica))
Garcelon, Nicolás (Université Paris Cité)
Hsieh, Elena (University of Colorado. Department of Pediatrics)
Leavis, Helen (Utrecht University. Department of Rheumatology and Clinical Immunology)
Lee, Seungwon (Boston Children's Hospital (Boston, Estats Units d'Amèrica))
Liu, Liangying (Virginia Tech)
Kusters, Maaike A. (Great Ormond Street Hospital for Children NHS Foundation Trust (Londres, Regne Unit))
Lloyd, Brian C. (Immune Deficiency Foundation (Maryland, Estats Units d'Amèrica))
Martinson, Alexandra K. (Children's National Hospital. Department of Pediatrics (Washington, Estats Units d'Amèrica))
Mester, Rachel (University of California. Department of Computational Medicine)
Moore, Justin B. (Wake Forest University. Department of Implementation Science (California, Estats Units d'Amèrica))
Moshous, Despina (Hôpital universitaire Necker-Enfants malades (París))
Orange, Jordan S. (Columbia University. Department of Pediatrics (New York, Estats Units d'Amèrica))
Parrish, Nefatia (Jeffrey Modell Foundation (New York, Estats Units d'Amèrica))
Parker, Sarah Henrickson (Virginia Tech Carilion School of Medicine. Department of Health Systems and Implementation Science)
Pasaniuc, Bogdan (University of Pennsylvania. Department of Genetics)
Peng, Xiao P. (The Children's Hospital at Montefiore (New York, Estats Units d'Amèrica))
Pergent, Martine (The International Patient Organisation for Primary Immunodeficiencies(Bèlgica))
Piera-Jiménez, Jordi (Servei Català de la Salut)
Quinn, Jessica (Jeffrey Modell Foundation (New York, Estats Units d'Amèrica))
Ramesh, Sidharth (Medblocks Inc (Estats Units d'Amèrica))
Roberts, Kirk (The University of Texas Health Science Center at Houston (Estats Units d'Amèrica))
Robinson, Peter N. (Charité-Universitätsmedizin Berlin)
Savova, Guergana (Harvard Medical School)
Scalchunes, Christopher (Immune Deficiency Foundation (Maryland, Estats Units d'Amèrica))
Seidel, Markus G. (Medical University of Graz (Àustria))
Simoneau, Rachel (Jeffrey Modell Foundation (New York, Estats Units d'Amèrica))
Soler Palacín, Pere (Vall d'Hebron Institut de Recerca (VHIR))
Sullivan, Kathleen (Children's Hospital of Philadelphia (Estats Units d'Amèrica))
Van Gijn, Marielle (Amsterdam UMC)
Wi, Chung-Il (Mayo Clinic (Rochester, Estats Units d'Amèrica))
Zhou, Dawei (Virginia Tech. Department of Computer Science (Estats Units d'Amèrica))
Tenembaum, Vanessa (Jeffrey Modell Foundation (New York, Estats Units d'Amèrica))
Butte, Manish J. (University of California. Department of Pediatrics)
Rider, Nicholas L. (Virginia Tech Carilion School of Medicine. Department of Health Systems and Implementation Science)

Data:	2025
Resum:	The use of artificial intelligence (AI) in inborn errors of immunity offers transformative potential in diagnostics and disease management but faces multiple challenges that were discussed at the second Artificial Intelligence in Primary Immunodeficiency conference, held in New York City (March 19-22, 2025). The conference addressed 7 themes: predictive diagnostic algorithms, health equity, industry collaboration, advanced computational tools like large language models, patient-led AI initiatives, multiomics integration, and implementation science. Discussions highlighted the growing impact of AI on diagnostics, genomics, and health systems, emphasizing the need for high-quality, diverse datasets and ethical safeguards to ensure equitable application. Participants stressed that AI alone cannot resolve systemic inequities or delays in diagnosis. Challenges such as the lack of harmonized datasets, the complexity of integrating multiomics data, ethical concerns, and the difficulty of adapting solutions to low-resource settings were emphasized. Additionally, the use implementation science was pointed out as one of the major challenges to ensure applicability and scalability in real-world settings. This requires overcoming resistance to adoption, addressing infrastructure gaps, and ensuring regulatory compliance. Collaboration across academia, clinicians, patients, regulators, and industry is essential to ensure AI delivers equitable, lasting benefits for individuals with inborn errors of immunity.
Nota:	Altres ajuts: acords transformatius de la UAB
Drets:	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, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Artificial intelligence ; Inborn errors of immunity ; Primary immunodeficiency ; Electronic health records ; Machine learning ; Large language models ; Health equity ; -omics ; Clinical decision support ; Implementation science ; Patient-centered AI ; AI scalability ; AI rare diseases
Publicat a:	The journal of allergy and clinical immunology, Vol. 157, Num. 2 (February 2025) , p. 307-315, ISSN 1097-6825

DOI: 10.1016/j.jaci.2025.09.002

9 p, 813.0 KB

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