The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which can be quantified as a biomarker. The objective of the study reported in this paper is to develop robust EEG-based biomarkers for detecting AD in its early stages. We present a new approach to quantify the slowing of the EEG, one of the most consistent features at different stages of dementia, based on changes in the EEG amplitudes (ΔEEG A ). The new approach has sensitivity and specificity values of 100% and 88.88%, respectively, and outperformed the Lempel-Ziv Complexity (LZC) approach in discriminating between AD and normal subjects.
KE Sharquie, AA Noaimi, E Abdulqader, WK Al-Janabi, J Dermatol Venereol, 2020 - Cited by 6
A survey statistician for cholera in Iraq for 1980 and until 2003 show that cholera is endemic in Iraq and that the highest number of casualties recorded in the years 1998-1999 and increasing spread of the disease during the wars in hot climates, wet a study bacteriological used where circles selective and tests Alkouhaoah examinations serological system
In this paper, a harvested prey-predator model involving infectious disease in prey is considered. The existence, uniqueness and boundedness of the solution are discussed. The stability analysis of all possible equilibrium points are carried out. The persistence conditions of the system are established. The behavior of the system is simulated and bifurcation diagrams are obtained for different parameters. The results show that the existence of disease and harvesting can give rise to multiple attractors, including chaos, with variations in critical parameters.
Background: Rheumatoid arthritis (RA) is a chronic and systemic autoimmune disease that is characterized by severe synovial inflammation, cartilage erosion, bone loss, and generalized vasculopathy. Although the immunologic mechanism of RA is still unclear, it is now thought to be a primarily Th17-driven disease. Along with other factors, IL-23 stimulates the expansion of Th17 cells from naive CD4+ T cells.
Objective: The objective of this study is to assess the circulating levels of interleukin (IL)-23 in rheumatoid arthritis (RA) and determine the correlation between plasma/serum IL-23 levels and disease activity. So, we performed a systematic review with meta-analysis comparing
... Show MoreCore decompression is one of the commonest used techniques in the handling of osteonecrosis of the pre-collapsed head of the femur. Core decompression had succeeded in preserving the hip joint and delaying the requisite for total hip replacement, but it had failed in the induction of osteogenesis in the necrotic area, thus augmenting core decompression with biological agents to induce osteogenic activity. To assess the effects of platelet-rich plasma in non-traumatic avascular necrosis of the hip joint (early stage) after core decompression. Interventional comparative study for twenty-four patients (32 hip joints) with AVN of the head of the femur was involved in this prospective study, and they were separated into two groups of 16
... Show MoreResearchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
... Show MoreThe use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th
... Show MoreSpraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...
The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
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