AUTHOR=Belhadi Asma , Holland Jon-Olav , Yazidi Anis , Srivastava Gautam , Lin Jerry Chun-Wei , Djenouri Youcef TITLE=BIoMT-ISeg: Blockchain internet of medical things for intelligent segmentation JOURNAL=Frontiers in Physiology VOLUME=13 YEAR=2023 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2022.1097204 DOI=10.3389/fphys.2022.1097204 ISSN=1664-042X ABSTRACT=

In the quest of training complicated medical data for Internet of Medical Things (IoMT) scenarios, this study develops an end-to-end intelligent framework that incorporates ensemble learning, genetic algorithms, blockchain technology, and various U-Net based architectures. Genetic algorithms are used to optimize the hyper-parameters of the used architectures. The training process was also protected with the help of blockchain technology. Finally, an ensemble learning system based on voting mechanism was developed to combine local outputs of various segmentation models into a global output. Our method shows that strong performance in a condensed number of epochs may be achieved with a high learning rate and a small batch size. As a result, we are able to perform better than standard solutions for well-known medical databases. In fact, the proposed solution reaches 95% of intersection over the union, compared to the baseline solutions where they are below 80%. Moreover, with the proposed blockchain strategy, the detected attacks reached 76%.