Asthma prediction across the human lifespan: a machine learning-based risk factor analysis

A quality of life and healthcare expenditures are both negatively affected by asthma. This review delves into the topic of asthma prediction by examining a range of risk variables, such as genetic susceptibility, environmental exposures, and lifestyle impacts. Following the data preparation that we provide to the model; machine learning algorithms will carry out the detection. The findings show that machine learning has great promise as a tool for healthcare providers to use in determining who are at risk of acquiring asthma and reshaping current methods of prevention. In order to improve upon the current state of the art, we suggest combining data mining with the Machine Learning algorithm and then comparing the results.