AIMC Topic: Neural Networks, Computer

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The Wisdom of Networks: A General Adaptation and Learning Mechanism of Complex Systems: The Network Core Triggers Fast Responses to Known Stimuli; Innovations Require the Slow Network Periphery and Are Encoded by Core-Remodeling.

BioEssays : news and reviews in molecular, cellular and developmental biology
I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the weakly connecte...

Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.

Molecules (Basel, Switzerland)
The automatic detection of diabetic retinopathy is of vital importance, as it is the main cause of irreversible vision loss in the working-age population in the developed world. The early detection of diabetic retinopathy occurrence can be very helpf...

Deep Learning in Microscopy Image Analysis: A Survey.

IEEE transactions on neural networks and learning systems
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a l...

Residual Convolutional Neural Network for the Determination of Status in Low- and High-Grade Gliomas from MR Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research
Isocitrate dehydrogenase () mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative r...

A Deep-Dream Virtual Reality Platform for Studying Altered Perceptual Phenomenology.

Scientific reports
Altered states of consciousness, such as psychotic or pharmacologically-induced hallucinations, provide a unique opportunity to examine the mechanisms underlying conscious perception. However, the phenomenological properties of these states are diffi...

The neuromorphological caudate-putaminal clustering of neostriate interneurons: Kohonen self-organizing maps and supervised artificial neural networks with multivariate analysis.

Journal of theoretical biology
AIMS: The objective of this study is to investigate the possibility of the neuromorphotopological clustering of neostriate interneurons (NSIN) and their consequent classification into caudate (CIN) and putaminal neuron type (PIN), according to the nu...

Statistics of Visual Responses to Image Object Stimuli from Primate AIT Neurons to DNN Neurons.

Neural computation
Under the goal-driven paradigm, Yamins et al. ( 2014 ; Yamins & DiCarlo, 2016 ) have shown that by optimizing only the final eight-way categorization performance of a four-layer hierarchical network, not only can its top output layer quantitatively p...

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

Biomedical engineering online
BACKGROUND: Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of...

Prediction of dose to the relatives of patients treated with radioiodine-131 using neural networks.

Journal of radiological protection : official journal of the Society for Radiological Protection
In this study, the effective dose received by the family members and caregivers of 52 thyroid cancer patients, who had been treated with radioiodine I-131, was measured to investigate the ability of the neural network to predict the doses to the rela...

Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: Our purpose was to use deep learning for the automated detection of age-related macular degeneration (AMD) in spectral domain optical coherence tomography (SD-OCT).