Laren D Tan, Nolan Nguyen, Enrique Lopez, Daniel Peverini, Mathew Shedd, Abdullah Alismail, H Bryant Nguyen
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The current research on AI applications in asthma care was then reviewed, including algorithms, AI-driven tools for personalized medicine, and digital platforms for patient engagement. Case studies and clinical trials assessing AI's impact on predictive accuracy and treatment adherence were reviewed. AI, particularly ML, enhances asthma management by analyzing data from wearables and patient records to predict exacerbations, stratify risk, and inform personalized treatment. Studies demonstrate AI's capability to recommend tailored interventions, monitor adherence through smart applications, and facilitate real-time treatment adjustments. Ethical challenges include ensuring patient trust, data security, and equitable technology access. In conclusion, AI's integration in asthma care holds significant promise for predictive interventions, personalized regimens, and continuous support, ultimately aiming to improve patient outcomes and reduce healthcare burdens. Continued advancements in AI will bridge current care gaps, fostering a patient-centric, proactive approach in asthma management.</p>","PeriodicalId":15079,"journal":{"name":"Journal of Asthma and Allergy","volume":"18 ","pages":"1179-1191"},"PeriodicalIF":3.0000,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12367921/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence in the Management of Asthma: A Review of a New Frontier in Patient Care.\",\"authors\":\"Laren D Tan, Nolan Nguyen, Enrique Lopez, Daniel Peverini, Mathew Shedd, Abdullah Alismail, H Bryant Nguyen\",\"doi\":\"10.2147/JAA.S535264\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Asthma, a chronic respiratory condition, impacts over 339 million individuals globally, including 25 million in the United States, contributing to significant morbidity and healthcare costs. Despite advances, challenges persist in managing exacerbations, ensuring medication adherence, and patient education. This narrative review explores the transformative potential of artificial intelligence (AI) in improving asthma management through predictive analytics, personalized treatment, and continuous patient engagement. A search of the United States National Library of Medicine's PubMed database was performed for articles pertaining to asthma and artificial intelligence, machine learning (ML), neural network, or deep learning. The current research on AI applications in asthma care was then reviewed, including algorithms, AI-driven tools for personalized medicine, and digital platforms for patient engagement. Case studies and clinical trials assessing AI's impact on predictive accuracy and treatment adherence were reviewed. AI, particularly ML, enhances asthma management by analyzing data from wearables and patient records to predict exacerbations, stratify risk, and inform personalized treatment. Studies demonstrate AI's capability to recommend tailored interventions, monitor adherence through smart applications, and facilitate real-time treatment adjustments. Ethical challenges include ensuring patient trust, data security, and equitable technology access. In conclusion, AI's integration in asthma care holds significant promise for predictive interventions, personalized regimens, and continuous support, ultimately aiming to improve patient outcomes and reduce healthcare burdens. Continued advancements in AI will bridge current care gaps, fostering a patient-centric, proactive approach in asthma management.</p>\",\"PeriodicalId\":15079,\"journal\":{\"name\":\"Journal of Asthma and Allergy\",\"volume\":\"18 \",\"pages\":\"1179-1191\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12367921/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Asthma and Allergy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/JAA.S535264\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"ALLERGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Asthma and Allergy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JAA.S535264","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ALLERGY","Score":null,"Total":0}
Artificial Intelligence in the Management of Asthma: A Review of a New Frontier in Patient Care.
Asthma, a chronic respiratory condition, impacts over 339 million individuals globally, including 25 million in the United States, contributing to significant morbidity and healthcare costs. Despite advances, challenges persist in managing exacerbations, ensuring medication adherence, and patient education. This narrative review explores the transformative potential of artificial intelligence (AI) in improving asthma management through predictive analytics, personalized treatment, and continuous patient engagement. A search of the United States National Library of Medicine's PubMed database was performed for articles pertaining to asthma and artificial intelligence, machine learning (ML), neural network, or deep learning. The current research on AI applications in asthma care was then reviewed, including algorithms, AI-driven tools for personalized medicine, and digital platforms for patient engagement. Case studies and clinical trials assessing AI's impact on predictive accuracy and treatment adherence were reviewed. AI, particularly ML, enhances asthma management by analyzing data from wearables and patient records to predict exacerbations, stratify risk, and inform personalized treatment. Studies demonstrate AI's capability to recommend tailored interventions, monitor adherence through smart applications, and facilitate real-time treatment adjustments. Ethical challenges include ensuring patient trust, data security, and equitable technology access. In conclusion, AI's integration in asthma care holds significant promise for predictive interventions, personalized regimens, and continuous support, ultimately aiming to improve patient outcomes and reduce healthcare burdens. Continued advancements in AI will bridge current care gaps, fostering a patient-centric, proactive approach in asthma management.
期刊介绍:
An international, peer-reviewed journal publishing original research, reports, editorials and commentaries on the following topics: Asthma; Pulmonary physiology; Asthma related clinical health; Clinical immunology and the immunological basis of disease; Pharmacological interventions and new therapies.
Although the main focus of the journal will be to publish research and clinical results in humans, preclinical, animal and in vitro studies will be published where they shed light on disease processes and potential new therapies.