Artificial intelligence (AI) continues to transform data analysis in many domains. Progress each domain is driven by a growing body of annotated data, increased computational resources, and technological innovations. In medicine, the sensitivity complexity tasks, potentially high stakes, requirement accountability give rise particular set challenges. this review, we focus on three key methodological approaches that address some challenges AI-driven medical decision making. 1) Explainable AI...

Emerging evidence suggests the presence of neuroanatomical abnormalities in subjects with autism spectrum disorder (ASD). Identifying anatomical correlates could thus prove useful for automated diagnosis ASD. Radiomic analyses based on MRI texture features have shown a great potential characterizing differences occurring from tissue heterogeneity, and identifying related to these differences. However, only limited number studies investigated link between image This paper proposes study grey...

Background: Colorectal cancer (CRC) is the third most common among men and women. Its diagnosis in early stages, typically done through analysis of colon biopsy images, can greatly improve chances a successful treatment. This paper proposes to use convolution neural networks (CNNs) predict three tissue types related progression CRC: benign hyperplasia (BH), intraepithelial neoplasia (IN), carcinoma (Ca). Methods: Multispectral images thirty CRC patients were retrospectively analyzed. Images...

To isolate the brain from non-brain tissues using a fully automatic method may be affected by presence of radio frequency non-homogeneity MR images (MRI), regional anatomy, sequences, and subjects study. In order to automate tumor (Glioblastoma) detection, we proposed novel approach skull stripping for axial slices derived MRI. Then, was detected multi-level threshold segmentation based on histogram analysis. Skull-stripping method, applied adaptive morphological operations approach. This is...

Abstract In this paper, we propose and demonstrate experimentally a new wireless digital encryption hyperchaotic communication system based on radio frequency (RF) protocols for secure real-time data or image transmission. A reconfigurable hardware architecture is developed to ensure the interconnection between two field programmable gate array development platforms through XBee RF modules. To synchronization of transmitter receiver, feedback masking technique dynamic modulation has been...

Predicting the survival outcome of patients with glioblastoma multiforme (GBM) is key importance to clinicians for selecting optimal course treatment. The goal this study was evaluate usefulness geometric shape features, extracted from MR images, as a potential non-invasive way characterize GBM tumours and predict overall times GBM.The data 40 were obtained Cancer Genome Atlas Imaging Archive. T1 weighted post-contrast fluid-attenuated inversion-recovery volumes co-registered segmented into...

Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images. Three types pathological tissues (PT) are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma. Materials Methods In proposed approach, region interest containing PT is first images active contour segmentation. then encoded based on Laplacian-of-Gaussian (LoG) filter, discrete wavelets (DW) gray level...

In this paper, we present a new network-on-chip (NoC) that handles accurate localizations of the faulty parts NoC. The proposed NoC is based on error detection mechanisms suitable for dynamic NoCs, where number and position processor elements or blocks vary during runtime. Indeed, propose online data packet adaptive routing algorithm errors. Both presented are able to distinguish permanent transient errors localize accurately (data bus, input port, output port) in routers, while preserving...

The ultimate focus of this paper is to provide a hyperchaos-based reconfigurable platform for the real-time securing communicating embedded systems interconnected in networks according Internet Things (IoT) standards. proposed platform’s Register Transfer Level (RTL) architecture entirely developed and designed from scratch using VHSIC Hardware Description Language (VHDL). original idea consists exploiting nonlinearity discretized optimized 4D Lorenz hyperchaotic system as an encryption...

When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step.This study examined three approaches (ANN, GA-ANN, ANFIS) for daily global radiation (GSR) in south Algeria: Adrar, Ouargla, Bechar.The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve ANN model.The ANFIS models performed better than standalone ANN-based with being suited forecasting all sites, it best values...

In this paper, we present a new deadlock-free fault-tolerant adaptive routing algorithm for the 2D mesh NoC interconnections. The main contribution of is that it allows both, messages in networks incorporating regions not necessarily rectangular, and to all nodes which are completely blocked by faulty nodes. proposed based on modified turn model well known XY algorithm. We detail basic principle algorithm, prove its deadlock freeness, feasibility efficiency through simulation results.

In this paper, we present a new approach for realtime FPGA implementation of the random key based Lorenz's chaotic generator data stream encryption. We propose structural hardware architecture designed small chip area and high speed performance. This is particularly attractive since it provides low-cost security telecommunication solution while holding or increasing encryption throughput rate. show its feasibility through which detailed presented using Virtex Xilinx FPGA. employs only 1926...