AIMC Topic: Neural Networks, Computer

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Fog Computing Employed Computer Aided Cancer Classification System Using Deep Neural Network in Internet of Things Based Healthcare System.

Journal of medical systems
Computer assisted automatic smart pattern analysis of cancer affected pixel structure takes critical role in pre-interventional decision making for oral cancer treatment. Internet of Things (IoT) in healthcare systems is now emerging solution for mod...

Finite-time nonfragile time-varying proportional retarded synchronization for Markovian Inertial Memristive NNs with reaction-diffusion items.

Neural networks : the official journal of the International Neural Network Society
The issue of synchronization for a class of inertial memristive neural networks over a finite-time interval is investigated in this paper. Specifically, reaction-diffusion items and Markovian jump parameters are both considered in the system model, m...

Existence and finite-time stability of discrete fractional-order complex-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
Without decomposing complex-valued systems into real-valued systems, the existence and finite-time stability for discrete fractional-order complex-valued neural networks with time delays are discussed in this paper. First of all, in order to obtain t...

Modeling aspects of the language of life through transfer-learning protein sequences.

BMC bioinformatics
BACKGROUND: Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary information. However, for some applica...

A temporal visualization of chronic obstructive pulmonary disease progression using deep learning and unstructured clinical notes.

BMC medical informatics and decision making
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients with COPD and to generate a t...

Representation learning for clinical time series prediction tasks in electronic health records.

BMC medical informatics and decision making
BACKGROUND: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, n...

Artificial intelligence in medical imaging.

Magnetic resonance imaging
The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how medical imaging is deployed. Artificial intelligence (AI) is potentially another such developmen...

CAD and AI for breast cancer-recent development and challenges.

The British journal of radiology
Computer-aided diagnosis (CAD) has been a popular area of research and development in the past few decades. In CAD, machine learning methods and multidisciplinary knowledge and techniques are used to analyze the patient information and the results ca...

Efficient network architecture search via multiobjective particle swarm optimization based on decomposition.

Neural networks : the official journal of the International Neural Network Society
The efforts devoted to manually increasing the width and depth of convolutional neural network (CNN) usually require a large amount of time and expertise. It has stimulated a rising demand of neural architecture search (NAS) over these years. However...

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.

NeuroImage
Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can delay its progression, no effective cures are available for AD. Accura...