Artificial intelligence in the diagnosis of pediatric allergic diseases. Issue 3 (11th December 2020)

• Record Type: Journal Article
• Authors: Ferrante, Giuliana; Licari, Amelia; Fasola, Salvatore; Marseglia, Gian Luigi; La Grutta, Stefania
• Editors: Peters, Rachel
• Is Part Of: Pediatric allergy and immunology. Volume 32:Issue 3(2021)
• Page Start: 405
• Page End: 413
• Publication Date: 2020-12-11
• Subjects: allergy -- artificial intelligence -- children -- diagnosis -- eczema -- food allergy -- respiratory allergy; Allergy in children -- Periodicals; Immunologic diseases in children -- Periodicals; 617
• DOI: 10.1111/pai.13419
• Languages: English
• ISSNs: 0905-6157

Abstract

Abstract: Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self‐care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In pediatric allergy research, the recent developments in AI approach provided new perspectives for characterizing the heterogeneity of allergic diseases among patients. Moreover, the increasing use of electronic health records and personal healthcare records highlighted the relevance of AI in improving data quality and processing and setting‐up advanced algorithms to interpret the data. This review aimed to summarize current knowledge about AI and discuss its impact on the diagnostic framework of pediatric allergic diseases such as eczema, food allergy, and respiratory allergy, along with the future opportunities that AI research can offer in this medical area.