Aggregated Pattern Classification Method for improving neural disorder stage detection.

Background: Neurological disorders pose a significant health challenge, and their early detection is critical for effective treatment planning and prognosis. Traditional classification of neural disorders based on causes, symptoms, developmental stage, severity, and nervous system effects has limitations. Leveraging artificial intelligence (AI) and machine learning (ML) for pattern recognition provides a potent solution to address these challenges.

Analyzing anonymous activities using Interrupt-aware Anonymous User-System Detection Method (IAU-S-DM) in IoT.

The intrusion detection process is important in various applications to identify unauthorized Internet of Things (IoT) network access. IoT devices are accessed by intermediators while transmitting the information, which causes security issues. Several intrusion detection systems are developed to identify intruders and unauthorized access in different software applications.

Optimizing lung cancer classification through hyperparameter tuning.

Artificial intelligence is steadily permeating various sectors, including healthcare. This research specifically addresses lung cancer, the world's deadliest disease with the highest mortality rate. Two primary factors contribute to its onset: genetic predisposition and environmental factors, such as smoking and exposure to pollutants.

Dietary caffeine intake is associated with favorable metabolic profile among apparently healthy overweight and obese individuals.

Background: Recent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.

Reseek-Arrhythmia: Empirical Evaluation of ResNet Architecture for Detection of Arrhythmia.

Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals' lives. Globally, arrhythmias are recognized as a significant health concern, accounting for nearly 12 percent of all deaths. As a result, there has been a growing focus on utilizing artificial intelligence for the detection and classification of abnormal heartbeats.

Automatic Diabetic Foot Ulcer Recognition Using Multi-Level Thermographic Image Data.

Lower extremity diabetic foot ulcers (DFUs) are a severe consequence of diabetes mellitus (DM). It has been estimated that people with diabetes have a 15% to 25% lifetime risk of acquiring DFUs which leads to the risk of lower limb amputations up to 85% due to poor diagnosis and treatment. Diabetic foot develops planter ulcers where thermography is used to detect the changes in the planter temperature.

Preventing overloaded dissemination in healthcare applications using NonDelay tolerant dissemination technique.

Wearable Sensors (WSs) are widely used in healthcare applications to monitor patient health. During the data transmission, dissemination requires additional time to transmit the details with minimum computation difficulties. The existing techniques consume high overloaded while transmitting data in healthcare applications.

Adaptive genetic algorithm for user preference discovery in multi-criteria recommender systems.

A Multi-Criteria Recommender System (MCRS) represents users' preferences on several factors of products and utilizes these preferences while making product recommendations. In recent studies, MCRS has demonstrated the potential of applying Multi-Criteria Decision Making methods to make effective recommendations in several application domains. However, eliciting actual user preferences is still a major challenge in MCRS since we have many criteria for each product.

Numerical and Experimental Analysis of Horizontal-Axis Wind Turbine Blade Fatigue Life.

Horizontal-axis wind turbines are the most popular wind machines in operation today. These turbines employ aerodynamic blades that may be oriented either upward or downward. HAWTs are the most common non-conventional source of energy generation.

Functions, mechanisms, and clinical applications of lncRNA LINC00857 in cancer pathogenesis.

Emerging data indicated that long noncoding RNAs (lncRNAs) are crucial players in the biological processes via regulating epigenetics, transcription, and protein translation. A novel lncRNA, LINC00857, was indicated to upregulate in several types of cancer. In addition, LINC00857 was functionally related to the modulation of the cancer-linked behaviors, including invasion, migration, proliferation, epithelial-mesenchymal transition (EMT), cell cycle, and apoptosis.

Supporting wound healing by mesenchymal stem cells (MSCs) therapy in combination with scaffold, hydrogel, and matrix; State of the art.

Non-healing wounds impose a huge annual cost on the survival of different countries and large populations in the world. Wound healing is a complex and multi-step process, the speed and quality of which can be changed by various factors. To promote wound healing, compounds such as platelet-rich plasma, growth factors, platelet lysate, scaffolds, matrix, hydrogel, and cell therapy, in particular, with mesenchymal stem cells (MSCs) are suggested.

Syndrome Pattern Recognition Method Using Sensed Patient Data for Neurodegenerative Disease Progression Identification.

Neurodegenerative diseases are a group of conditions that involve the progressive loss of function of neurons in the brain and spinal cord. These conditions can result in a wide range of symptoms, such as difficulty with movement, speech, and cognition. The causes of neurodegenerative diseases are poorly understood, but many factors are believed to contribute to the development of these conditions.

Deep-EEG: An Optimized and Robust Framework and Method for EEG-Based Diagnosis of Epileptic Seizure.

Detecting brain disorders using deep learning methods has received much hype during the last few years. Increased depth leads to more computational efficiency, accuracy, and optimization and less loss. Epilepsy is one of the most common chronic neurological disorders characterized by repeated seizures.

Impact of endogenous stress on albumin structure in systemic lupus erythematosus (SLE) patients.

Systemic lupus erythematosus (SLE) is an inflammatory, autoimmune disorder of unknown etiology. The inflammatory stress in SLE patients may modify macromolecules and produce structural/functional abnormalities. The present study is aimed at examining the consequences of stresses on the structure of albumin in SLE patients.

Oral antimicrobial peptides: Types and role in the oral cavity.

Antimicrobial peptides (AMPs) are a wide-ranging class of host-defense molecules that act early to contest against microbial invasion and challenge. These are small cationic peptides that play an important in the development of innate immunity. In the oral cavity, the AMPs are produced by the salivary glands and the oral epithelium and serve defensive purposes.

Advances in Nanotechnology for Restorative Dentistry.

Rationalizing has become a new trend in the world of science and technology. Nanotechnology has ascended to become one of the most favorable technologies, and one which will change the application of materials in different fields. The quality of dental biomaterials has been improved by the emergence of nanotechnology.