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155 articles for “brain”
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Studying the effects of Exposure to Chemicals on The brain and Nervous System and The risk of Chemical Pollution
Abstract: Scientific research and studies on chemical pollution show that exposure of the brain and nervous system to chemicals causes serious damage ranging from cognitive, motor, and nerve cell disorders to chronic diseases such as Alzheimer's and neurological paralysis. These substances (such as lead ions, mercury, solvents that combine and dissolve easily in the blood, and pesticides) disrupt neurotransmitters and cause cell damage, especially during the early stages of body development. …
Published in International Journal of Brain Sciences · Vol. 3, Issue 1, 2026 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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Neural Implants & Brain–Computer Interfaces: Enhancing Human Intelligence or Violating Free Will?
Abstract: The integration of neural implants with artificial intelligence creates opportunities to develop new implants and enhance current nanotechnologies. Although these advances hold significant potential for restoring neurological functions, they also introduce important ethical concerns. The rapid advancements in neural implants and brain–computer interfaces [BCIs] are revolutionizing human cognition, enabling enhanced intelligence, communication, and even thought-driven control of external devices. Although these technologies offer great promise in enhancing human abilities, they …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 13–18 Read article
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Brain And Gesture Controlled Assistive System For Physically Challenged Individuals
Abstract: Assistive communication technologies are essential for improving the independence of individuals with physical and sensory disabilities. This paper presents the design and implementation of a multimodal assistive system that integrates brain signal acquisition and gesture recognition for real- time communication. The system utilizes an Electroencephalography (EEG) sensor to capture neural activity and a PAJ7620 gesture sensor along with an ADXL335 accelerometer to detect hand movements. The acquired signals are processed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 Read article
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Detection and Classification of Brain Tumor from MRI And CT Images using Harmony Search Optimization and Deep Learning
Abstract: Primary brain tumor detection and classification are critical factors in ensuring effective treatment and, ultimately, improving patient well-being. This paper describes a novel method for detecting and classifying brain tumors with the help of magnetic resonance imaging (MRI) and computed tomography (CT) images. The suggested method combines harmony search optimization (HSO) and Convolution Neural Networks (CNN) based on deep learning techniques, yielding an impressive accuracy rate of 99.13% for both …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 31–49 Read article
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Strengthening Neurological and Familial Interventions: Adult Coping Following Pediatric Brain Injury and Comorbidity
Abstract: Background: Pediatric traumatic brain injury (PTBI) contributes to long-term physical, cognitive, and emotional difficulties and is a major cause of mortality and disability in children. An estimated 200,000 fatalities in India each year are attributed to traumatic brain injuries, with PTBI accounting for a significant share of these cases. Accidents, abuse, and sports injuries are just a few of the causes of post-traumatic brain injury (PTBI), which can result in …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 2, Issue 2, 2024 · pp. 7–15 Read article
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Yoga and Neural Health: Enhancing Brain Function Through Postural Alignment
Abstract: Correct posture significantly influences neural function and brain health by ensuring optimal alignment of the spine and nervous system. Poor posture disrupts neural communication, impairs blood flow, and affects cerebrospinal fluid (CSF) circulation, leading to adverse effects on cognitive performance, emotional regulation, and overall brain health. This study examines the physiological connection between posture and neural health, emphasizing its impact on cognitive function, mood, and neuroplasticity. Using a mixed-methods approach, …
Published in Recent Trends in Sports · Vol. 2, Issue 1, 2025 · pp. 24–28 Read article
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Omega-3 Fatty Acids and Brainpower: The Role of Seafood Consumption
Abstract: The following article talks about the strong link between eating seafood and brain health, focusing on the role of omega-3 fatty acids, especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), in supporting brain development, function, and longevity. The article uses new research to show how these important polyunsaturated fatty acids help the brain in ways like memory, learning, focus, and attention. It also reduces the chance of developing dementia, Alzheimer's, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 1, 2025 · pp. 15–29 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Mind-Gut Connection: The Psychosomatic Effects of Stress and Emotions on Digestive System
Abstract: Stress, understood as an immediate disruption to bodily equilibrium, triggers an adaptive or allostatic response that impacts gastrointestinal function both in the short and long term. The enteric nervous system communicates in both directions with the brain through parasympathetic and sympathetic pathways, collectively forming what is known as the brain-gut axis. Unani scholars describe stress as a response to the loss of something valuable, such as an opportunity, a desired …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 1, 2025 · pp. 11–14 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Rosemary: A Natural Way to Improve Brain Health and Cognitive Function
Abstract: Cognitive decline is a common consequence of aging, often leading to diminished quality of life. Although conventional drug treatments, such as anticholinesterase inhibitors, are available for managing cognitive decline, they are not always effective in older adults and may even induce adverse effects. As a result, there has been growing interest in natural alternatives, particularly traditional herbal medicines, for their potential cognitive-enhancing properties. Among these, Rosmarinus officinalis (Rosemary) has gained …
Published in International Journal of Brain Sciences · Vol. 2, Issue 1, 2025 · pp. 30–36 Read article
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Detection of Brain Tumors from MRI Images Based On Development of Thinking Computer Systems Techniques
Abstract: Brain tumors are one of the common diseases of the nervous system and have great harm to human health, and even lead to death. The detection, segmentation, and extraction of contaminated tumour regions from Magnetic Resonance Imaging (MRI) pictures are major problems; yet, a repetitive and time-consuming task performed by radiologists or clinical experts relies on their experience. The many anatomical structures of the human organ can be imagined using …
Published in Current Trends in Signal Processing Read article
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Artificial Intelligence in Cerebellum Activation
Abstract: Neuroscience plays a significant function during the progression of artificial intelligence. It provided inspiration for the development of human-like AI. There are two ways that neuroscience encourages us to develop AI systems. Neural networks that replicate human cognition and those that match the structure of the brain are the two objectives. Neural networks, which draw inspiration from the architecture of the human brain, are the engine behind contemporary artificial intelligence …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 14–26 Read article
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Deciphering the Pathophysiology of Migraine: Understanding Trigeminovascular System Activity and the Importance of the Gut-Brain Axis
Abstract: Migraine, a prevalent and disabling neurological condition, manifests in distinct phases: premonitory, aura, headache, postdrome, and interictal. Being a primary contributor to adult disability, it presents a substantial economic challenge on a global scale. Even with extensive research spanning centuries, the complete grasp of its root causes continues to evade us. This intricate neurovascular disorder primarily involves local vasodilation of intracranial and extracerebral blood vessels, coupled with simultaneous stimulation of …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 50–61 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article