Asthma Detection and Management using Artificial Intelligence: A Review

Asthma is one of the respiratory diseases that is chronic and has millions of patients across the globe. Diagnosis and management are still not easy with its natural variations, and the restriction of the conventional clinical instruments. The review covers the current and future uses of AI in asthma management with special reference to the possibility of improving patient outcomes. The analysis identifies the role of AI in assisting the diagnosis, forecasting, and customization of treatment under the assistance of various types of data. These data sources are electronic health records (EHRs), data of wearable devices, environmental factors, and respiratory sounds. Furthermore, the paper will address key technical, ethical, and practical challenges that are not allowing AI to be widely used. Among these issues, there are problems and challenges to data privacy, algorithm bias, and poor and universally-applicable models. The promising solutions to be mentioned along with the Federated Learning and Explainable AI (XAI) are named as the main items of the further research. Lastly, the paper proposes a vision of patient centered, and proactive, asthma management with the use of AI capabilities.