RFCPredicModel: Prediction Algorithm of Precision Medicine in Healthcare with Big Data

Devising innovative healthcare algorithms provides the medical practitioners to save lives and a better support in the decision making and also time saving in crucial moment. The Objective of this research paper is to develop and present an innovative algorithm, RFCPredicModel, for precision medicine in heart disease prediction with aid to the medical history of the patient. By leveraging big data analytics techniques with a diverse set of healthcare data, including genomics and clinical records, objective is to accurately classify individuals as having or not having heart disease. Originality in the RFCPredicModel is by integrating the mentioned features in the algorithm to handle missing data, normalize features, and select informative attributes for accurate prediction. It utilizes a comprehensive dataset from a benchmarked machine learning repository, showcasing its originality in the context of precision medicine. The algorithm’s ability to outperform traditional methods and achieve high accuracy in heart disease prediction demonstrates its potential accurate prediction for healthcare professionals in providing personalized treatment plans.