A Systematic Literature Survey on A Smart Multidisease Prediction and Doctor Recommendations using ML

Smart multidisease prediction and doc- tor recommendations using machine learning is a growing field of research. The proposed methodol- ogy seeks to deliver precise illness prediction for several diseases, which may have important reper- cussions for enhancing the precision and timeli- ness of medical diagnostics and improving patient outcomes. Machine learning algorithms like Naive Bayesian networks,CNN, KNN are used to properly predict and classify diseases based on patient symp- toms and medical data analysis. Several studies have proposed models that can predict multiple diseases such as diabetes, heart disease, chronic kidney dis- ease, and cancer. The ultimate goal is to provide healthcare practitioners with the tools to make ed- ucated decisions and deliver improved patient care. This paper presents a survey of research papers and articles on the topic of smart multidisease prediction and doctor recommendations using machine learn- ing.