End-to-end predictive intelligence diagnosis in brain tumor using lightweight neural network

In this paper, a novel brain tumor end-to-end detection approach based on predictive intelligence using lightweight neural network is presented in practical application in medical data center in hospital and can be beneficial for smart healthcare. While medical intelligence diagnosis has received much attention from academia, little effort has been made in predictive brain tumor intelligence diagnosis and the issue of practical use have been largely overlooked. The technique we applied is referred to as deep learning and predictive intelligence. Firstly, a novel end-to-end brain tumor detection based on lightweight neural network instead of common neural network is utilized in our network to realize the trade-off between the accuracy and efficiency. Secondly, in addition to predictive intelligence, edge intelligence is also adopted in our architecture to make it more easily deployed and dealt with data processing in medical data center in hospital in practical application and balance a lot of resources. Several sets of experiments have carried out to test the validity of brain tumor intelligence diagnosis and it has demonstrated that it is promising and similar to the state-of-the art. The research has resulted in a solution of medical predictive intelligence diagnosis and it proves to be encouraging. It has contributed to our present understanding of practical application of intelligence diagnosis on the pioneer work. (C) 2021 Published by Elsevier B.V.