Most of the deaths and health spending in the world are as a result of chronic conditions like diabetes, cardiovascular diseases and cancer. Diagnosis at early stages is very critical in the process of curbing on the advancement and complications of these diseases. As the healthcare data explodes, machine learning (ML) offers a formidable force to the discovery of hidden patterns, which can be used in predictive analytics leading to early diagnosis. In this paper, the supervised ML algorithms will be tested on medical data aiming at the identification of the chronic diseases. The findings showed that the type of the ensemble methods seeds averagely better compared to the individual learners in the cases and they portray the future of the ML based prediction models on early development of diagnosis skills and the healthcare sector able to intervene on time when it is needed.
Veerendra Nath Jasthi (Fri,) studied this question.