ArticleThe Journal of allergy and clinical immunology2026
Proceedings of the second Artificial Intelligence in Primary Immunodeficiency (AIPI) meeting.
Article in The Journal of allergy and clinical immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Building alliances for early detection of immunodeficiencies: from primary care to hematology.Frontiers in immunology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
43 authors.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.