Neural Networks

Neural networks are computer algorithms which imitate the functioning of the human brain in order to recognize patterns and solve complex problems with high accuracy. They are used in a variety of applications, including image recognition, autonomous driving, natural language processing, and data analysis. Neural networks are powerful tools that can significantly improve the accuracy and speed of data processing. They can also be employed to create predictions, helping to make decisions based on large amounts of data.

← Journal of Nervous System and Physiological Phenomena

Related Articles

10 article(s) found

Perception Threshold Variations of Pain Area with Herpetic Ophthalmic Neuralgia

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Biocompatible Scaffolds for Human-Induced Pluripotent Stem Cell Transplantation and Modeling Post-Stroke Recovery in Three-Dimensional Neural Cell Culture

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A Bit Exagerrated Role of Complete Blood Count Parameters on the Prognosis of Idiopathic Sudden Sensorineural Hearing Loss

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Dual Effects of Neuroprotection and Neurotoxicity by General Anesthetics on Neural Stem Cells: Role of Autophagy

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Suboccipital Decompression for Occipital Neuralgia

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Biological Networks: An Introductory Review

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Trigeminal Neuralgia: Indications of Gasserian Ganglion Gompression with Balloon Catheter in the Modern Era

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Artificial Neural Network Model for Rainfall Data Analysis During 2004-2017 in Tamil Nadu, India – Prevailing Pattern Evaluation on Climate Change

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Genetic Algorithm Coupled with Neural Networks to Guesstimate the Subsurface Features of the Earth

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New Classification for Bifurcated Mandibular Neural Canal

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