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The evolution of Big Data in neuroscience and neurology
Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years,...
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Could artificial intelligence have consciousness? Some perspectives from neurology and parapsychology
The possibility of AI consciousness depends much on the correct answer to the mind–body problem: how our materialistic brain generates subjective...
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Executive Function and Intelligent Goal-Directed Behavior: Perspectives from Psychology, Neurology, and Computer Science
The concept of executive function, as top-down control of processes, originated in computer science in the 1950s. However, it has since become an...
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Artificial Intelligence: A Bridge Between Psychoanalysis and Neurology The Psi-Organ in a Nutshell
To be able to merge the psyche with the neural system has been a long-sought goal. There is much scientific literature on results from research on...
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Intuitiveness and Trustworthiness of AI-Powered Interfaces for Neurological Diagnosis - Preliminary Results
The work presented in this article is part of a broader research initiative whose focus revolves around the integration of Artificial Intelligence...
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Principles of Description
Information systems, which include computers and the Ψ-organ, can be described on the one hand from the point of view of physics or neurology and on...
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Unraveling the intricacies of EEG seizure detection: A comprehensive exploration of machine learning model performance, interpretability, and clinical insights
In neurology, it is critical to promptly and precisely identify epileptic episodes using EEG data. Interpretability and thorough model evaluation are...
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Identifying patients in need of psychological treatment with language representation models
Early diagnosis of psychological disorders is very important for patients to regain their health. Research shows that many patients do not realize...
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Surface EEG based epileptic seizure detection using wavelet based features and dynamic mode decomposition power along with KNN classifier
The seizure is defined as the sudden synchronous activity of the number of neurons resulting in abnormal body symptoms. This paper proposes a...
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A CNN-LSTM hybrid network for automatic seizure detection in EEG signals
Epilepsy is a chronic neurological disorder. Epileptics are prone to sudden seizures that cause disruptions in their daily lives. The separation of...
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A machine learning approach for multiple sclerosis diagnosis through Detecron Architecture
Multiple sclerosis is a prevalent inflammatory disease affecting the central nervous system, leading to demyelination. Neuroradiology relies on...
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Virtual reality applied to physiotherapy: a review of current knowledge
Technological innovations have enabled physiotherapy to apply new possibilities in the rehabilitation of patients, especially in the use of virtual...
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Modeling Magnetic Resonance Imaging and X-Rays by Executing Artificial Neural Networks
This chapter acquaints you with the practical application of computer vision and artificial neural networks in neurology and radiology. In it, you...
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Named Entity Recognition in Portuguese Neurology Text Using CRF
Automatic recognition of named entities from clinical text lightens the work of health professionals by hel** in the interpretation and easing...
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A Question and Answering System for Mental Health of the Elderly Based on BiLSTM-CRF Model and Knowledge Graph
Currently, the aging population in China is becoming increasingly severe. Research has shown that 85% of the elderly have varying degrees of...
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Detection of idiopathic normal pressure hydrocephalus on head CT using a deep convolutional neural network
Idiopathic normal pressure hydrocephalus (iNPH) is an underrecognized cause of dementia, with reasons for underdiagnosis including symptomatic...
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Meta Attention-Generation Network for Cross-Granularity Few-Shot Learning
Fine-grained classification with few labeled samples has urgent needs in practice since fine-grained samples are more difficult and expensive to...
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World of Hardware: Neuroscience and More
Understanding the functional model of the Ψ-organ requires knowledge of both, computer engineering and neurology. Hardware languages are addressed,...
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Visual Modeling of Multiple Sclerosis Patient Pathways: The Healthcare Workers’ Perspectives
Multiple Sclerosis (MS) necessitates tailored care along intricate pathways throughout a patient's lifetime. Visualizing these pathways enhances the...
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Interactive Visualization of 3D CNN Relevance Maps to Aid Model Comprehensibility
Relevance maps derived from convolutional neural networks (CNN) indicate the influence of a particular image region on the decision of the CNN model....