With the continuous advancement of information technology

big data and artificial intelligence have become increasingly sophisticated and are now widely used in the medical field. In recent years

leveraging the support of big data

cloud computing

and related technologies

machine learning-based predictive models have seen extensive application in disease prognosis and healthcare. The use of Spark big data technology can effectively combine big data with artificial intelligence technology and assist doctors in establishing disease risk prediction models for cases

implementing intelligent diagnosis

prediction

and decision-making

and deeply applying medical big data to further verify the feasibility of big data in the medical field. This article focuses on the technical advantages of the Spark platform

pointing out its high-performance analysis capabilities in medical prediction

rich machine learning libraries

and real-time analysis capabilities. After establishing a disease prediction model

there are still shortcomings and issues that need to be addressed in order to further optimize the model.