AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Hippocampus

Showing 61 to 70 of 180 articles

Clear Filters

Deep learning-based diagnosis of temporal lobe epilepsy associated with hippocampal sclerosis: An MRI study.

Epilepsy research
PURPOSE: The currently available indicators-sensitivity and specificity of expert radiological evaluation of MRIs-to identify mesial temporal lobe epilepsy (MTLE) associated with hippocampal sclerosis (HS) are deficient, as they cannot be easily asse...

Identification of Alzheimer associated differentially expressed gene through microarray data and transfer learning-based image analysis.

Neuroscience letters
Major factors contribute to mental stress and enhance the progression of late-onset Alzheimer's disease (AD). The factors that lead to neurodegeneration, such as tau protein hyperphosphorylation and increased amyloid-beta production, can be mimicked ...

Deep learning and radiomics based automatic diagnosis of hippocampal sclerosis.

The International journal of neuroscience
Accurate and rapid segmentation of the hippocampus can help doctors perform intractable temporal lobe epilepsy (TLE) preoperative evaluations to identify good surgical candidates. This study aims to establish a radiomics system for the automatic diag...

Toward the biological model of the hippocampus as the successor representation agent.

Bio Systems
The hippocampus is an essential brain region for spatial memory and learning. Recently, a theoretical model of the hippocampus based on temporal difference (TD) learning has been published. Inspired by the successor representation (SR) learning algor...

The structural aspects of neural dynamics and information flow.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Neurons have specialized structures that facilitate information transfer using electrical and chemical signals. Within the perspective of neural computation, the neuronal structure is an important prerequisite for the versatile computatio...

[A spatial localization model of mobile robot based on entorhinal-hippocampal cognitive mechanism in rat brain].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Physiological studies reveal that rats rely on multiple spatial cells for spatial navigation and memory. In this paper, we investigated the firing mechanism of spatial cells within the entorhinal-hippocampal structure of the rat brain and proposed a ...

Hippocampal formation-inspired probabilistic generative model.

Neural networks : the official journal of the International Neural Network Society
In building artificial intelligence (AI) agents, referring to how brains function in real environments can accelerate development by reducing the design space. In this study, we propose a probabilistic generative model (PGM) for navigation in uncerta...

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects.

Human brain mapping
Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus,...

Hippocampal representations for deep learning on Alzheimer's disease.

Scientific reports
Deep learning offers a powerful approach for analyzing hippocampal changes in Alzheimer's disease (AD) without relying on handcrafted features. Nevertheless, an input format needs to be selected to pass the image information to the neural network, wh...

Normalized unitary synaptic signaling of the hippocampus and entorhinal cortex predicted by deep learning of experimental recordings.

Communications biology
Biologically realistic computer simulations of neuronal circuits require systematic data-driven modeling of neuron type-specific synaptic activity. However, limited experimental yield, heterogeneous recordings conditions, and ambiguous neuronal ident...