{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:43:52Z","timestamp":1776185032820,"version":"3.50.1"},"reference-count":59,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:p>Wheezing is a common condition in childhood, and its prevalence has increased in the last decade. Up to one-third of preschoolers develop recurrent wheezing, significantly impacting their quality of life and healthcare resources. Artificial Intelligence (AI) technologies have recently been applied in paediatric allergology and pulmonology, contributing to disease recognition, risk stratification, and decision support. Additionally, the COVID-19 pandemic has shaped healthcare systems, resulting in an increased workload and the necessity to reduce access to hospital facilities. In this view, AI and Machine Learning (ML) approaches can help address current issues in managing preschool wheezing, from its recognition with AI-augmented stethoscopes and monitoring with smartphone applications, aiming to improve parent-led\/self-management and reducing economic and social costs. Moreover, in the last decade, ML algorithms have been applied in wheezing phenotyping, also contributing to identifying specific genes, and have been proven to even predict asthma in preschoolers. This minireview aims to update our knowledge on recent advancements of AI applications in childhood wheezing, summarizing and discussing the current evidence in recognition, diagnosis, phenotyping, and asthma prediction, with an overview of home monitoring and tele-management.<\/jats:p>","DOI":"10.3389\/fmed.2024.1460050","type":"journal-article","created":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T16:11:17Z","timestamp":1724775077000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Artificial intelligence and wheezing in children: where are we now?"],"prefix":"10.3389","volume":"11","author":[{"given":"Laura","family":"Venditto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sonia","family":"Morano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michele","family":"Piazza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Zaffanello","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Tenero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giorgio","family":"Piacentini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuliana","family":"Ferrante","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2024,8,27]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"S13","DOI":"10.1016\/j.earlhumdev.2013.07.017","article-title":"Wheezing in preschool children","volume":"89","author":"Tenero","year":"2013","journal-title":"Early Hum Dev"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1949","DOI":"10.1016\/j.jaci.2020.12.643","article-title":"Burden of preschool wheeze and progression to asthma in the UK: population-based cohort 2007 to 2017","volume":"147","author":"Bloom","year":"2021","journal-title":"J Allergy Clin Immunol"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1002\/ppul.20644","article-title":"Prevalence of asthma-like symptoms in young children","volume":"42","author":"Bisgaard","year":"2007","journal-title":"Pediatr Pulmonol"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"974","DOI":"10.1136\/thx.2007.093187","article-title":"Associations of wheezing phenotypes in the first 6 years of life with atopy, lung function and airway responsiveness in mid-childhood","volume":"63","author":"Henderson","year":"2008","journal-title":"Thorax"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1056\/NEJM199501193320301","article-title":"Asthma and wheezing in the first six years of life","volume":"332","author":"Martinez","year":"1995","journal-title":"N Engl J Med"},{"key":"ref6","first-page":"1","article-title":"National surveillance of asthma: United States, 2001-2010","volume":"3","author":"Moorman","year":"2012","journal-title":"Vital Health Stat"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1111\/j.1398-9995.2005.00692.x","article-title":"Evaluation of cost of disease: assessing the burden to society of asthma in children in the European Union","volume":"60","author":"Van Den Akker-van Marle","year":"2005","journal-title":"Allergy"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1111\/resp.13842","article-title":"Artificial intelligence as an emerging diagnostic approach in paediatric pulmonology","volume":"25","author":"Ferrante","year":"2020","journal-title":"Respirology"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1111\/pai.13419","article-title":"Artificial intelligence in the diagnosis of pediatric allergic diseases","volume":"32","author":"Ferrante","year":"2021","journal-title":"Pediatr Allergy Immunol"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1111\/pai.13624","article-title":"Machine learning: A modern approach to pediatric asthma","volume":"33","author":"Cilluffo","year":"2022","journal-title":"Pediatr Allergy Immunol"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1080\/03091902.2024.2321846","article-title":"Artificial intelligence and machine learning responses to COVID-19 related inquiries","volume":"47","author":"Zaeri","year":"2023","journal-title":"J Med Eng Technol"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1034\/j.1399-3003.2000.16d04.x","article-title":"When a \u201cwheeze\u201d is not a wheeze: acoustic analysis of breath sounds in infants","volume":"16","author":"Elphick","year":"2000","journal-title":"Eur Respir J"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"242","DOI":"10.17305\/bjbms.2012.2447","article-title":"A survey on automated wheeze detection systems for asthmatic patients","volume":"12","author":"Shaharum","year":"2012","journal-title":"Bosn J Basic Med Sci"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1370\/afm.3039","article-title":"Home monitoring of asthma exacerbations in children and adults with use of an AI-aided stethoscope","volume":"21","author":"Emeryk","year":"2023","journal-title":"Ann Fam Med"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"5750","DOI":"10.3390\/s23125750","article-title":"StethAid: A digital auscultation platform for pediatrics","volume":"23","author":"Arjoune","year":"2023","journal-title":"Sensors"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1186\/s12931-020-01523-9","article-title":"Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes","volume":"21","author":"Kevat","year":"2020","journal-title":"Respir Res"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1186\/1471-2431-14-257","article-title":"Validation of computerized wheeze detection in young infants during the first months of life","volume":"14","author":"Puder","year":"2014","journal-title":"BMC Pediatr"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"2170","DOI":"10.1088\/0967-3334\/37\/12\/2170","article-title":"Computerized wheeze detection in young infants: comparison of signals from tracheal and chest wall sensors","volume":"37","author":"Puder","year":"2016","journal-title":"Physiol Meas"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1183\/09031936.03.00036302","article-title":"Wheeze monitoring in children for assessment of nocturnal asthma and response to therapy","volume":"21","author":"Bentur","year":"2003","journal-title":"Eur Respir J"},{"key":"ref20","first-page":"1304","article-title":"Wheeze detection in the pediatric intensive care unit: comparison among physician, nurses, respiratory therapists, and a computerized respiratory sound monitor","volume":"53","author":"Prodhan","year":"2008","journal-title":"Respir Care"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"e28865","DOI":"10.2196\/28865","article-title":"Wheeze recognition algorithm for remote medical care device in children: validation study","volume":"4","author":"Habukawa","year":"2021","journal-title":"JMIR Pediatr Parent"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1186\/s40814-021-00917-w","article-title":"The impact of a digital wheeze detector on parental disease management of pre-school children suffering from wheezing-a pilot study","volume":"7","author":"Dramburg","year":"2021","journal-title":"Pilot Feasibility Stud"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"00518","DOI":"10.1183\/23120541.00518-2023","article-title":"Clinical efficacy and satisfaction of a digital wheeze detector in a multicentre randomised controlled trial: the WheezeScan study","volume":"10","author":"Do","year":"2024","journal-title":"ERJ Open Res"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"106278","DOI":"10.1016\/j.cct.2021.106278","article-title":"The diagnosis of respiratory disease in children using a phone-based cough and symptom analysis algorithm: the smartphone recordings of cough sounds 2 (SMARTCOUGH-C 2) trial design","volume":"101","author":"Moschovis","year":"2021","journal-title":"Contemp Clin Trials"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1002\/ppul.25801","article-title":"Development and technical validation of a smartphone-based pediatric cough detection algorithm","volume":"57","author":"Kruizinga","year":"2022","journal-title":"Pediatr Pulmonol"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"240182","DOI":"10.1155\/2013\/240182","article-title":"An intelligent system approach for asthma prediction in symptomatic preschool children","volume":"2013","author":"Chatzimichail","year":"2013","journal-title":"Comput Math Methods Med"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1080\/17476348.2023.2271832","article-title":"Phenotype and endotype based treatment of preschool wheeze","volume":"17","author":"Salehian","year":"2023","journal-title":"Expert Rev Respir Med"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1016\/S2213-2600(15)00428-2","article-title":"Childhood asthma prediction models: a systematic review","volume":"3","author":"Smit","year":"2015","journal-title":"Lancet Respir Med"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1164\/ajrccm.162.4.9912111","article-title":"A clinical index to define risk of asthma in young children with recurrent wheezing","volume":"162","author":"Castro-Rodr\u00edguez","year":"2000","journal-title":"Am J Respir Crit Care Med"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.jaip.2012.10.008","article-title":"Evaluation of the modified asthma predictive index in high-risk preschool children","volume":"1","author":"Chang","year":"2013","journal-title":"J Allergy Clin Immunol Pract"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1183\/09031936.03.00005903","article-title":"Predicting persistent disease among children who wheeze during early life","volume":"22","author":"Kurukulaaratchy","year":"2003","journal-title":"Eur Respir J"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1016\/j.jaci.2009.06.045","article-title":"Predicting the long-term prognosis of children with symptoms suggestive of asthma at preschool age","volume":"124","author":"Caudri","year":"2009","journal-title":"J Allergy Clin Immunol"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"320","DOI":"10.3389\/fped.2019.00320","article-title":"Predicting asthma using clinical indexes","volume":"7","author":"Castro-Rodriguez","year":"2019","journal-title":"Front Pediatr"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.jaci.2013.06.002","article-title":"A simple asthma prediction tool for preschool children with wheeze or cough","volume":"133","author":"Pescatore","year":"2014","journal-title":"J Allergy Clin Immunol"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1016\/j.jaip.2014.08.009","article-title":"Optimum predictors of childhood asthma: persistent wheeze or the asthma predictive index?","volume":"2","author":"Amin","year":"2014","journal-title":"J Allergy Clin Immunol Pract"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1164\/rccm.201408-1537OC","article-title":"Exhaled biomarkers and gene expression at preschool age improve asthma prediction at 6 years of age","volume":"191","author":"Klaassen","year":"2015","journal-title":"Am J Respir Crit Care Med"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"e2234714","DOI":"10.1001\/jamanetworkopen.2022.34714","article-title":"Development of a symptom-based tool for screening of children at high risk of preschool asthma","volume":"5","author":"Reyna","year":"2022","journal-title":"JAMA Netw Open"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2013\/435321","article-title":"Predicting asthma outcome using partial Least Square regression and artificial neural networks","volume":"2013","author":"Chatzimichail","year":"2013","journal-title":"Adv Artif Intellig"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"e12076","DOI":"10.1002\/clt2.12076","article-title":"Development of childhood asthma prediction models using machine learning approaches","volume":"11","author":"Kothalawala","year":"2021","journal-title":"Clin Transl Allergy"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"75","DOI":"10.3390\/jpm12010075","article-title":"Integration of genomic risk scores to improve the prediction of childhood asthma diagnosis","volume":"12","author":"Kothalawala","year":"2022","journal-title":"J Pers Med"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"e14062","DOI":"10.1111\/pai.14062","article-title":"Understanding progression from pre-school wheezing to school-age asthma: can modern data approaches help?","volume":"34","author":"Custovic","year":"2023","journal-title":"Pediatr Allergy Immunol"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1016\/j.jaip.2018.09.016","article-title":"Phenotypes of recurrent wheezing in preschool children: identification by latent class analysis and utility in prediction of future exacerbation","volume":"7","author":"Fitzpatrick","year":"2019","journal-title":"J Allergy Clin Immunol Pract"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1186\/s12890-018-0593-9","article-title":"Automated chart review utilizing natural language processing algorithm for asthma predictive index","volume":"18","author":"Kaur","year":"2018","journal-title":"BMC Pulm Med"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1111\/all.15849","article-title":"Current state and prospects of artificial intelligence in allergy","author":"Van Breugel","year":"2023","journal-title":"Allergy"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1111\/coin.12427","article-title":"Generating and evaluating cross\u2010sectional synthetic electronic healthcare data: preserving data utility and patient privacy.","author":"Wang","year":"2021","journal-title":"Comput Intell"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1080\/13696998.2023.2277072","article-title":"How AI is advancing asthma management? Insights into economic and clinical aspects","author":"Al Meslamani","year":"2023","journal-title":"J Med Eco"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s12325-023-02743-3","article-title":"Machine learning approaches to predict asthma exacerbations: a narrative review.","author":"Molfino","year":"2024","journal-title":"Adv Ther"},{"key":"ref48","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.1093\/ije\/30.6.1473","article-title":"Avon longitudinal study of parents and children. Risk factor associations with wheezing patterns in children followed longitudinally from birth to 3(1\/2) years","volume":"30","author":"Sherriff","year":"2001","journal-title":"Int J Epidemiol"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.1016\/j.jaci.2011.02.002","article-title":"Comparison of childhood wheezing phenotypes in 2 birth cohorts: ALSPAC and PIAMA","volume":"127","author":"Savenije","year":"2011","journal-title":"J Allergy Clin Immunol"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1016\/j.jaci.2019.10.026","article-title":"Characterization of longitudinal wheeze phenotypes from infancy to adolescence in project viva, a prebirth cohort study","volume":"145","author":"Sordillo","year":"2020","journal-title":"J Allergy Clin Immunol"},{"key":"ref51","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1164\/rccm.201810-1956CI","article-title":"Childhood asthma: advances using machine learning and mechanistic studies","volume":"199","author":"Saglani","year":"2019","journal-title":"Am J Respir Crit Care Med"},{"key":"ref52","doi-asserted-by":"publisher","first-page":"1935","DOI":"10.1016\/j.jaci.2016.08.046","article-title":"Latent class analysis reveals clinically relevant atopy phenotypes in 2 birth cohorts","volume":"139","author":"Hose","year":"2017","journal-title":"J Allergy Clin Immunol"},{"key":"ref53","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1164\/rccm.201801-0190OC","article-title":"Longitudinal phenotypes of respiratory health in a high-risk urban birth cohort","volume":"199","author":"Bacharier","year":"2019","journal-title":"Am J Respir Crit Care Med"},{"key":"ref54","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1016\/j.jaci.2013.05.041","article-title":"Joint modeling of parentally reported and physician-confirmed wheeze identifies children with persistent troublesome wheezing","volume":"132","author":"Belgrave","year":"2013","journal-title":"J Allergy Clin Immunol"},{"key":"ref55","doi-asserted-by":"publisher","first-page":"2617","DOI":"10.1016\/j.jaip.2020.02.032","article-title":"Heterogeneity of mild to moderate persistent asthma in children: confirmation by latent class analysis and association with 1-year outcomes","volume":"8","author":"Fitzpatrick","year":"2020","journal-title":"J Allergy Clin Immunol Pract"},{"key":"ref56","doi-asserted-by":"publisher","first-page":"2024","DOI":"10.1111\/all.13439","article-title":"Childhood asthma clusters reveal neutrophil-predominant phenotype with distinct gene expression","volume":"73","author":"Su","year":"2018","journal-title":"Allergy"},{"key":"ref57","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1111\/cea.13553","article-title":"Longitudinal trajectories of severe wheeze exacerbations from infancy to school age and their association with early-life risk factors and late asthma outcomes","volume":"50","author":"Deliu","year":"2020","journal-title":"Clin Exp Allergy"},{"key":"ref58","doi-asserted-by":"publisher","first-page":"e36070","DOI":"10.1097\/MD.0000000000036070","article-title":"Identification of biomarkers associated with pediatric asthma using machine learning algorithms: A review","volume":"102","author":"Lin","year":"2023","journal-title":"Medicine"},{"key":"ref59","doi-asserted-by":"publisher","first-page":"627337","DOI":"10.3389\/fped.2021.627337","article-title":"Real-world verification of artificial intelligence algorithm-assisted auscultation of breath sounds in children","volume":"9","author":"Zhang","year":"2021","journal-title":"Front Pediatr"}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2024.1460050\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T16:11:24Z","timestamp":1724775084000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2024.1460050\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,27]]},"references-count":59,"alternative-id":["10.3389\/fmed.2024.1460050"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2024.1460050","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,27]]},"article-number":"1460050"}}