Machine learning models can predict the spread of diseases by analyzing historical data and identifying factors that influence transmission. These models can be trained to recognize patterns in data, such as the correlation between environmental factors and disease outbreaks. This capability is particularly useful for emerging infectious diseases, where rapid response is crucial. Machine learning can also be used to develop predictive models for chronic diseases, aiding in early diagnosis and personalized treatment plans.
