AIMC Topic: Neural Networks, Computer

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Virtual Interpolation Images of Tumor Development and Growth on Breast Ultrasound Image Synthesis With Deep Convolutional Generative Adversarial Networks.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: We sought to generate realistic synthetic breast ultrasound images and express virtual interpolation images of tumors using a deep convolutional generative adversarial network (DCGAN).

Estimation and validation of individualized dynamic brain models with resting state fMRI.

NeuroImage
A key challenge for neuroscience is to develop generative, causal models of the human nervous system in an individualized, data-driven manner. Previous initiatives have either constructed biologically-plausible models that are not constrained by indi...

Effect of color information on the diagnostic performance of glaucoma in deep learning using few fundus images.

International ophthalmology
PURPOSE: The purpose of this study was to evaluate the accuracy of the convolutional neural network (CNN) model in glaucoma identification with three primary colors (red, green, blue; RGB) and split color channels using fundus photographs with a smal...

Analysis of high-dimensional genomic data using MapReduce based probabilistic neural network.

Computer methods and programs in biomedicine
BACKGROUND: The size of genomics data has been growing rapidly over the last decade. However, the conventional data analysis techniques are incapable of processing this huge amount of data. For the efficient processing of high dimensional datasets, i...

Interactive thyroid whole slide image diagnostic system using deep representation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The vast size of the histopathology whole slide image poses formidable challenges to its automatic diagnosis. With the goal of computer-aided diagnosis and the insights that suspicious regions are generally easy to identify...

Skull shape reconstruction using cascaded convolutional networks.

Computers in biology and medicine
Designing a cranial implant to restore the protective and aesthetic function of the patient's skull is a challenging process that requires a substantial amount of manual work, even for an experienced clinician. While computer-assisted approaches with...

Role of artificial intelligence and vibrational spectroscopy in cancer diagnostics.

Expert review of molecular diagnostics
INTRODUCTION: Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These tech...

Learning personalized ADL recognition models from few raw data.

Artificial intelligence in medicine
Recognition of activities of daily living (ADL) is an essential component of assisted living systems based on actigraphy. This task can nowadays be performed by machine learning models which are able to automatically extract and learn relevant featur...

Sparse coding with a somato-dendritic rule.

Neural networks : the official journal of the International Neural Network Society
Cortical neurons are silent most of the time: sparse activity enables low-energy computation in the brain, and promises to do the same in neuromorphic hardware. Beyond power efficiency, sparse codes have favourable properties for associative learning...

Stability of delayed inertial neural networks on time scales: A unified matrix-measure approach.

Neural networks : the official journal of the International Neural Network Society
This note introduces a unified matrix-measure concept to study the stability of a class of inertial neural networks with bounded time delays on time scales. The novel matrix-measure concept unifies the classic matrix-measure and the generalized matri...