Analysing BP Disease Prediction through Transfer Learning (machine learning) - A Conceptual Framework and Case Study

In the evolving landscape of the clever healthcare industry, the detection and prognostication of ailments thru technological improvements present each possibility and demanding situations, mainly within the realm of lethal tumors. This paper delves into the application of switch getting to know in the framework of the Internet of Medical Things (IoMT) to enhance the accuracy and reliability of disease predictions. Utilizing the modernA capabilities of the Google Net deep device-learning version, we introduce a relaxed IoMT-based totally technique that substantially outperforms conventional methodologies in predicting lethal most cancers ailments. Our have a study demonstrates a incredible accuracy price of 90 seven.5%, underscoring the ability of switch learning to revolutionize predictive diagnostics within the clever healthcare area. By integrating superior IoMT gadgets and secure information protocols, this method no longer most effective improves illness prediction quotes but moreover addresses important privacy and protection issues inherent in modern scientific information handling.