A Robust medical data sharing application with a collaborative hypothesis and Elastic net regression model

Clinical data and records are the main data to help various customized applications like clinical proof, protection, digital data and criminal personality. Different blockchain and conventional methodology have been created, which are obsolete in this example. Progressed clinical information imparting to security and protection are along these lines required in saving related procedures. This study develops an adaptive blockchain approach and a machine-learning model based on elastic net regression. The preceding two ways give the classified data of brain cancer in the general hospital of Sowjanya greater safety and privacy. This is better than previous mechanisms, with precision 98.56%, detection rate 97.34%, error rate 0.023, sensitivity 98.38% and output 97.28% competing with existing approaches.