EEG Signal Classification Using Convolutional Neural Networks on Combined Spatial and Temporal Dimensions for BCI Systems.

EEG signal classification is an important task to build an accurate Brain Computer Interface (BCI) system. Many machine learning and deep learning approaches have been used to classify EEG signals. Besides, many studies have involved the time and frequency domain features to classify EEG signals.

Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks.

Machine learning algorithms are currently being implemented in an escalating manner to classify and/or predict the onset of some neurodegenerative diseases; including Alzheimer's Disease (AD); this could be attributed to the fact of the abundance of data and powerful computers. The objective of this work was to deliver a robust classification system for AD and Mild Cognitive Impairment (MCI) against healthy controls (HC) in a low-cost network in terms of shallow architecture and processing. In this study, the dataset included was downloaded from the Alzheimer's disease neuroimaging initiative (ADNI).

Protein Subcellular Localization Prediction Based on Internal Micro-similarities of Markov Chains.

Elucidating protein subcellular localization is an essential topic in proteomics research due to its importance in the process of drug discovery. Unfortunately, experimentally uncovering protein subcellular targets is an arduous process that may not result in a successful localization. In contrast, computational methods can rapidly predict protein subcellular targets and are an efficient alternative to experimental methods for unannotated proteins.

Studying the effects of haplotype partitioning methods on the RA-associated genomic results from the North American Rheumatoid Arthritis Consortium (NARAC) dataset.

The human genome, which includes thousands of genes, represents a big data challenge. Rheumatoid arthritis (RA) is a complex autoimmune disease with a genetic basis. Many single-nucleotide polymorphism (SNP) association methods partition a genome into haplotype blocks.

Comparative study for haplotype block partitioning methods - Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset.

Haplotype-based methods compete with "one-SNP-at-a-time" approaches on being preferred for association studies. Chromosome 6 contains most of the known genetic biomarkers for rheumatoid arthritis (RA) disease. Therefore, chromosome 6 serves as a benchmark for the haplotype methods testing.

Motor imagery based brain computer interface using transform domain features.

Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements.

Efficient rendering of digitally reconstructed radiographs on heterogeneous computing architectures using central slice theorem.

Digitally reconstructed radiographs (DRRs) play a significant role in modern clinical radiation therapy. They are used to verify patient alignments during image guided therapies with 2D-3D image registration. The generation of DRRs can be implemented intuitively in O(N3) relying on direct volume rendering (DVR) methods, such as ray marching.

Parallel generation of digitally reconstructed radiographs on heterogeneous multi-GPU workstations.

The growing importance of three-dimensional radiotherapy treatment has been associated with the active presence of advanced computational workflows that can simulate conventional x-ray films from computed tomography (CT) volumetric data to create digitally reconstructed radiographs (DRR). These simulated x-ray images are used to continuously verify the patient alignment in image-guided therapies with 2D-3D image registration. The present DRR rendering pipelines are quite limited to handle huge imaging stacks generated by recent state-of-the-art CT imaging modalities.

Identification of rheumatoid arthritis biomarkers based on single nucleotide polymorphisms and haplotype blocks: A systematic review and meta-analysis.

Genetics of autoimmune diseases represent a growing domain with surpassing biomarker results with rapid progress. The exact cause of Rheumatoid Arthritis (RA) is unknown, but it is thought to have both a genetic and an environmental bases. Genetic biomarkers are capable of changing the supervision of RA by allowing not only the detection of susceptible individuals, but also early diagnosis, evaluation of disease severity, selection of therapy, and monitoring of response to therapy.

GPU acceleration for digitally reconstructed radiographs using bindless texture objects and CUDA/OpenGL interoperability.

This paper features an advanced implementation of the X-ray rendering algorithm that harnesses the giant computing power of the current commodity graphics processors to accelerate the generation of high resolution digitally reconstructed radiographs (DRRs). The presented pipeline exploits the latest features of NVIDIA Graphics Processing Unit (GPU) architectures, mainly bindless texture objects and dynamic parallelism. The rendering throughput is substantially improved by exploiting the interoperability mechanisms between CUDA and OpenGL.

Accelerating DRR generation using Fourier slice theorem on the GPU.

Digitally Reconstructed Radiographs (DRRs) play a vital role in medical imaging procedures and radiotherapy applications. They allow the continuous monitoring of patient positioning during image guided therapies using multi-dimensional image registration. Conventional generation of DRRs using spatial domain algorithms such as ray casting is associated with computational complexity of O(N(3)).

Genetic Case-Control Study for Eight Polymorphisms Associated with Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease which has a significant socio-economic impact. The aim of the current study was to investigate eight candidate RA susceptibility loci to identify the associated variants in Egyptian population. Eight single nucleotide polymorphisms (SNPs) (MTHFR-C677T and A1298C, TGFβ1 T869C, TNFB A252G, and VDR-ApaI, BsmI, FokI, and TaqI) were tested by genotyping patients with RA (n = 105) and unrelated controls (n = 80).

Effect of MTHFR, TGFβ1, and TNFB polymorphisms on osteoporosis in rheumatoid arthritis patients.

Diseases of the immune and the skeletal systems should be studied together for the deep interaction between them. Many studies consider osteoporosis (OP) as a risk factor for the prediction of disease progression in rheumatoid arthritis (RA). The aim of this research is to study the effect of four single nucleotide polymorphisms (SNPs) on RA patients with and without OP.

High Performance GPU-Based Fourier Volume Rendering.

Fourier volume rendering (FVR) is a significant visualization technique that has been used widely in digital radiography. As a result of its 𝒪(N (2)log⁡N) time complexity, it provides a faster alternative to spatial domain volume rendering algorithms that are 𝒪(N (3)) computationally complex. Relying on the Fourier projection-slice theorem, this technique operates on the spectral representation of a 3D volume instead of processing its spatial representation to generate attenuation-only projections that look like X-ray radiographs.

The design of 3D scaffold for tissue engineering using automated scaffold design algorithm.

Several progresses have been introduced in the field of bone regenerative medicine. A new term tissue engineering (TE) was created. In TE, a highly porous artificial extracellular matrix or scaffold is required to accommodate cells and guide their growth in three dimensions.

Interactive telemedicine solution based on a secure mHealth application.

In dynamic healthcare environments, caregivers and patients are constantly moving. To increase the healthcare quality when it is necessary, caregivers need the ability to reach each other and securely access medical information and services from wherever they happened to be. This paper presents an Interactive Telemedicine Solution (ITS) to facilitate and automate the communication within a healthcare facility via Voice over Internet Protocol (VOIP), regular mobile phones, and Wi-Fi connectivity.

An integrated evaluation for the performance of clinical engineering department.

Performance benchmarking have become a very important component in all successful organizations nowadays that must be used by Clinical Engineering Department (CED) in hospitals. Many researchers identified essential mainstream performance indicators needed to improve the CED's performance. These studies revealed mainstream performance indicators that use the database of a CED to evaluate its performance.