This paper presents a novel exploration of 5G (wire-free) communication and IoT technologies in healthcare, emphasizing their transformative potential. The global market for healthcare Internet of Things (IoT) is expanding rapidly, projected to grow from USD 139.74 billion in 2023 to USD 822.54 billion by 2032. As healthcare systems worldwide evolve, India’s healthcare sector, with only 2.3% of its GDP allocated to health, still faces significant challenges. However, it also identifies critical issues that need innovative solutions to fully harness the potential of these advancements. It highlights the significant advancements in wire-free solutions, enabling more efficient and accessible healthcare services. Early detection of cardiovascular problems is a major difficulty in the medical field. This work uses machine learning approaches to improve the accuracy of heart disease prediction. The following five algorithms, logistic regression, random forest, K-nearest neighbor, Naïve Bayes, and proposed AB are used, together with Cleveland dataset. GridSearchCV, fivefold cross-validation, and model accuracy optimization are used. GridSearchCV with fivefold cross-validation is used for hyperparameter optimization, selecting the optimal model parameters, and evaluating performance with precision in this work. .