Proceedings from the inaugural Artificial Intelligence in Primary Immune Deficiencies (AIPID) conference.

Rivière, Jacques G; Soler Palacín, Pere; Butte, Manish J

Rivière, Jacques G; Soler Palacín, Pere; Butte, Manish J.

Afiliación

Rivière JG; Infection and Immunity in Pediatric Patients Research Group, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; Pediatric Infectious Diseases and Immunodeficiencies Unit, Hospital Infantil i de la Dona, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; Jeffrey Modell Diagnostic and Research Center for Primary Immunodeficiencies, Barcelona, Spain; Universitat Autònoma de Barcelona, Barcelona, Spain.
Soler Palacín P; Infection and Immunity in Pediatric Patients Research Group, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; Pediatric Infectious Diseases and Immunodeficiencies Unit, Hospital Infantil i de la Dona, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; Jeffrey Modell Diagnostic and Research Center for Primary Immunodeficiencies, Barcelona, Spain; Universitat Autònoma de Barcelona, Barcelona, Spain.
Butte MJ; Division of Immunology, Allergy, and Rheumatology, Department of Pediatrics, University of California Los Angeles, Los Angeles, Calif; Department of Microbiology, Immunology, and Molecular Genetics, University of California Los Angeles, Los Angeles, Calif; Department of Human Genetics, University of California Los Angeles, Los Angeles, Calif. Electronic address: mbutte@mednet.ucla.edu.

J Allergy Clin Immunol ; 153(3): 637-642, 2024 Mar.

Article en En | MEDLINE | ID: mdl-38224784

ABSTRACT

ABSTRACT

Here, we summarize the proceedings of the inaugural Artificial Intelligence in Primary Immune Deficiencies conference, during which experts and advocates gathered to advance research into the applications of artificial intelligence (AI), machine learning, and other computational tools in the diagnosis and management of inborn errors of immunity (IEIs). The conference focused on the key themes of expediting IEI diagnoses, challenges in data collection, roles of natural language processing and large language models in interpreting electronic health records, and ethical considerations in implementation. Innovative AI-based tools trained on electronic health records and claims databases have discovered new patterns of warning signs for IEIs, facilitating faster diagnoses and enhancing patient outcomes. Challenges in training AIs persist on account of data limitations, especially in cases of rare diseases, overlapping phenotypes, and biases inherent in current data sets. Furthermore, experts highlighted the significance of ethical considerations, data protection, and the necessity for open science principles. The conference delved into regulatory frameworks, equity in access, and the imperative for collaborative efforts to overcome these obstacles and harness the transformative potential of AI. Concerted efforts to successfully integrate AI into daily clinical immunology practice are still needed.

Asunto(s)

Inteligencia Artificial; Enfermedades de Inmunodeficiencia Primaria; Humanos; Aprendizaje Automático; Procesamiento de Lenguaje Natural; Recolección de Datos

Palabras clave

Artificial intelligence; diagnosis; electronic health records; ethics; inborn errors of immunity; large language models; machine learning; natural language processing

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Enfermedades de Inmunodeficiencia Primaria Aspecto: Equity_inequality / Ethics Límite: Humans Idioma: En Revista: J Allergy Clin Immunol Año: 2024 Tipo del documento: Article País de afiliación: España Pais de publicación: Estados Unidos

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