A Framework for Augmented Intelligence in Allergy and Immunology Practice and Research-A Work Group Report of the AAAAI Health Informatics, Technology and Education Committee

Authors

Paneez Khoury, Laboratory of Allergic Diseases, NIAID, Bethesda, Md. Electronic address: khouryp@nih.gov.
Renganathan Srinivasan, The Vancouver Clinic, Vancouver, Wash.
Sujani Kakumanu, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin School of Medicine and Public Health and the William S. Middleton Veterans Memorial Hospital, Madison, Wisc.
Sebastian Ochoa, National Institutes of Infectious and Allergic Diseases, Bethesda, Md; Laboratory of Clinical Immunology and Microbiology, NIAID, Bethesda, Md.
Anjeni Keswani, Division of Allergy/Immunology, George Washington University School of Medicine and Health Sciences, Washington, DC.
Rachel Sparks, National Institutes of Infectious and Allergic Diseases, Bethesda, Md; Laboratory of Immune System Biology, NIAID, Bethesda, Md.
Nicholas L. Rider, Section of Immunology, Allergy and Retrovirology and the William T. Shearer Center for Human Immunobiology, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas.

Document Type

Journal Article

Publication Date

3-14-2022

Journal

The journal of allergy and clinical immunology. In practice

DOI

10.1016/j.jaip.2022.01.047

Keywords

Artificial intelligence; Asthma; Atopic dermatitis; Augmented intelligence; Clinical decision support; Electronic health records; Equity; Machine learning; Medical education; Natural language processing; Primary immunodeficiency

Abstract

Artificial and augmented intelligence (AI) and machine learning (ML) methods are expanding into the health care space. Big data are increasingly used in patient care applications, diagnostics, and treatment decisions in allergy and immunology. How these technologies will be evaluated, approved, and assessed for their impact is an important consideration for researchers and practitioners alike. With the potential of ML, deep learning, natural language processing, and other assistive methods to redefine health care usage, a scaffold for the impact of AI technology on research and patient care in allergy and immunology is needed. An American Academy of Asthma Allergy and Immunology Health Information Technology and Education subcommittee workgroup was convened to perform a scoping review of AI within health care as well as the specialty of allergy and immunology to address impacts on allergy and immunology practice and research as well as potential challenges including education, AI governance, ethical and equity considerations, and potential opportunities for the specialty. There are numerous potential clinical applications of AI in allergy and immunology that range from disease diagnosis to multidimensional data reduction in electronic health records or immunologic datasets. For appropriate application and interpretation of AI, specialists should be involved in the design, validation, and implementation of AI in allergy and immunology. Challenges include incorporation of data science and bioinformatics into training of future allergists-immunologists.

APA Citation

Khoury, Paneez; Srinivasan, Renganathan; Kakumanu, Sujani; Ochoa, Sebastian; Keswani, Anjeni; Sparks, Rachel; and Rider, Nicholas L., "A Framework for Augmented Intelligence in Allergy and Immunology Practice and Research-A Work Group Report of the AAAAI Health Informatics, Technology and Education Committee" (2022). GW Authored Works. Paper 595.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/595

Department

Medicine