Promoting the Public Health by Medical Image Analysis and Disease Diagnosis

Abstract

Public health has improved as a result of data analysis tools since they make disease identification early and simple. In the absence of data analysis methods, medical professionals' judgement is the only means of identifying the illness. This could be problematic in places without access to skilled medical professionals, which could ultimately result in the illness patient's death. Data analysis techniques are currently being applied in numerous medical disease detection situations in order to address the aforementioned challenges. The methods for detecting blood disorders are presented in this article. This model detects blood disorder disease using a blood smear in addition to a clinical report. The sick patients are classified using an ML classifier after an ML model extracts information from blood smear images and combines them with clinical features.