ABSTRACT
Disease prediction has been revolutionized in medical imaging and diagnostics by fusing machine learning techniques. This method uses Naive Bayes to improve healthcare outcomes via the delivery of reliable and efficient disease categorization using imaging data. This paper introduces an innovative approach, termed Enhanced Naive Bayes (ENB), and aimed at augmenting disease classification and doctor recommendation systems within the medical imaging domain. Here, we provide a method for disease type prediction using submitted photos and the improved Naive Bayes classification algorithm. A strong foundation for automated image-based disease categorization is provided by the use of machine learning methods, with a focus on improved Naive Bayes. The design of the system includes steps such as picture preprocessing, feature extraction, training an improved Naive Bayes classifier for accurate disease prediction. We want to help improve medical diagnoses by using this method, which combines machine learning with image processing, to its fullest potential.
