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627 articles for “neural”
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Stem Cell Therapy for Parkinson's Disease: Past, Present and Future
Abstract: Parkinson’s disease (PD) is one of the most common chronic progressive nervous system disorders of aging. Cell degeneration and death of dopamine neurons (DA neurons) in the substantial nigra, is the underlying feature of PD. Genetic studies showed much about the physiological processes associated with this disease. Replacing the cells lost by injury or disease has become a central idea aiming at the development of novel therapy for neurodegenerative diseases. …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 1, 2019 · pp. 1–12 Read article
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Effect of Ultrasound and Low Level Laser Therapy on Nerve Conduction Studies in Patients with Carpal Tunnel Syndrome
Abstract: Carpal tunnel syndrome is a common entrapment neuropathy resulting from median nerve compression with the symptoms of pain, numbness and tingling in the hand and fingers. There are many conservative treatment options available for carpal tunnel syndrome. Ultrasound and low level LASER therapy are found to be one of the effective conservative treatments. The purpose of this study is to find the effect of ultrasound and low level LASER therapy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 3, Issue 2, 2013 · pp. 9–14 Read article
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Physiotherapeutic Challenges in Treatment of Lumbar Spinal Stenosis: A Review
Abstract: Background: Lumbar spinal stenosis is one of the most common diseases in the elderly. It is characterized by narrowing of the spinal canal creating compression of the neural structures causing a constellation of symptoms that may include low back pain, lower extremity radiculopathy, neurogenic claudication, and gait impairment. LSS is the most frequent reason for spinal surgery in elderly people. But knowledge about the effectiveness, in particular of the conservative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 7, Issue 2, 2017 · pp. 6–12 Read article
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Behavioral and Electrophysiological Correlates of Semantic Processing in Kannada
Abstract: Semantics is one of the fundamentals of language components, encoding of which helps in understanding the meaning of the spoken or written language. The processing pattern of semantics has been studied extensively in different languages using either the conventional psycholinguistic experiments or advanced neuroimaging techniques. Previous studies have documented the behavioral and electrophysiological correlates of semantic processing in different languages. However, the correlation between these measures has not been well …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 2, 2019 · pp. 1–9 Read article
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An overview on the diagnosis and approaches in pharmacological management of Parkinson’s disease
Abstract: Parkinson’s disease (PD) might be a mutual neurodegenerative disease considered by a movement disorder containing rest tremor, bradykinesia, rigidity, and postural instability, and second-leading reason of dementia and is categorized by an advanced loss of dopaminergic neurons within the neural structure alongside the occurrence of intraneuronal α-synuclein-positive enclosures. PD is identified where bradykinesia happens along with rigidity or tremor within the existence of supporting features. The diagnosis is clinical, and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 11, Issue 1, 2021 · pp. 1–8 Read article
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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Ashaya as Abode: Reconciling Ayurvedic Vata Theory with Intestinal Neurophysiology
Abstract: Background-Ashaya refers to a site or structure within the body where a substance resides. Ashaya refers to the internal sites or structures within the body where various substances reside Commonly, seven Ashayas are described in males, while in females there are eight, while Sharangadhara has described 9 Ashayas. Vatashaya denotes the specific site of Vata Dosha, which is considered the chief among the three Doshas due to its vital role …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 2, 2026 · pp. 12–20 Read article
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Interrelationship Between Psychological Stress and Gastrointestinal Physiology: Role of the Gut–Brain Axis
Abstract: The relationship between stress and gut microbiome is a critical area of medical research underscoring the relativity and impact of psychological and emotional states on gastrointestinal (GI) health. This paper investigates the intricate relationship between stress and digestive health by analysing the influence of stress hormones, gut–brain interactions, and psychosocial determinants. Both acute and long-standing stress responses may disrupt normal gastrointestinal activity, affecting motility, secretion, intestinal microbiota, and overall digestive …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 2, 2026 · pp. 30–35 Read article
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Generative AI-Driven Design Optimization of Lightweight Polymer Composites for Electric Vehicles
Abstract: Lightweight polymer composites are increasingly important for electric vehicles, where mass reduction must be achieved without compromising structural performance, thermal stability, manufacturability, or material reliability. This study develops a generative AI-driven inverse-design framework for identifying experimentally credible lightweight polymer-composite configurations under coupled EV-oriented constraints. Public experimental polymer-composite datasets were integrated through leakage-controlled preprocessing and group-aware validation. A multi-task neural surrogate predicted mechanical response, while a conditional variational autoencoder explored feasible …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Cognitive Polymer Composite Systems for Autonomous Biomedical Response
Abstract: Cognitive polymer composite systems: A novel form of intelligent biomaterials with the capability to sense, process and respond to real time physiological stimuli on their own. The present paper offers a comprehensive platform to integrate stimulus responsive polymers with intrinsic sensing networks and learning based decision models to offer adaptable bio-medical solutions. Mathematical formulations are available that are used to model stimulus response behavior, sensor signal processing and cognition decision …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Wireless Biosensing Polymer Composites for Smart Healthcare Devices
Abstract: The wireless biosensing polymer composites have been found as one of the possible solutions in developing flexible, real-time and intelligent healthcare monitoring systems. Biomimic polymer matrices coupled with conductive nanomaterials can be used to design an understanding of physiological signals (strain, pressure, and temperature) that are highly sensitive and adaptable sensors. The attachment of these sensors to wireless communication systems, such as the Bluetooth Low Energy and Wi-Fi, eases the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 14, 2026 Read article
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AI-Optimized Biodegradable Polymer Composites for Medical Applications
Abstract: The value of biodegradable polymer composites in the medical practice has been massive as the composites may be deployed to provide temporary structural support, and they are also safe to degrade within the human body. However, the conventional material design process is trial and error, which is ineffective and inefficient. The article proposes a hybrid model involving experimental characterization, as well as an artificial intelligence (AI)-based model, to optimize biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision
Abstract: The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment. This paper describes a machine vision design, which incorporates convolutional neural networks, transformer models, and ensemble learning to correctly detect and localize material defects. The proposed system takes advantage of the capabilities of high-resolution imaging, advanced preprocessing software, and deep feature learning in the identification of the intricate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Motors Using a Deep Learning-Based Torque Control with Torque Ripple Reduction under Nonlinear Magnetic Conditions
Abstract: This research discusses a deep learning strategy for torque management to minimize the effect of torque ripple in a nonlinear electric motor. Nonlinear electric motor losses may include: magnetic saturation, harmonic flux losses and inverter losses. In many cases when the system parameters deviate and/or instability issues occur, the traditional method with a model-based approach or PI control may encounter challenges. In this case, the authors proposed a hybrid approach …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Artificial Intelligence-Based Optimization of Mechanical and Biocompatible Properties in Polymer Composite Implants
Abstract: Artificial Intelligence (AI) has already become a ground-breaking tool of streamlining polymer composite implants to enhance both mechanical strength and biocompatibility simultaneously. This paper recommend an AI-based multi-objective optimization model, which integrates the selection of materials, structural modelling, and biological evaluation. The in vitro biocompatibility indicators, including cytotoxicity and cell adhesion, can be used to model mechanical behavior, e.g. stress-strain behavior and fatigue behavior. To arrive at an optimal material …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Brain Stroke Detection Using Deep Learning and Grad-CAM Explainability Framework
Abstract: Seconds matter when a brain stroke occurs; it is a race against time where rapid, precise intervention is the only way to preserve a patient’s quality of life. This research introduces a deep learning framework designed to act as a vital ally for clinicians, providing automated, high-speed stroke detection through brain MRI analysis. At the heart of our approach is EfficientNetB0, a sophisticated neural network chosen for its ability to …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 8–14 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
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Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article