Researchers from Vellore Institute of Technology have introduced a hybrid approach using genetic algorithms and metaheuristic optimization with random forests to predict heart disease with 92% accuracy. The study, published in Scientific Reports, demonstrates how refined feature selection can improve diagnostic precision, offering a practical example for enhanced clinical decision-making.