AIMC Topic: Neural Networks, Computer

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Evaluation of Commonly Used Algorithms for Thyroid Ultrasound Images Segmentation and Improvement Using Machine Learning Approaches.

Journal of healthcare engineering
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis and the body's sensitivity to other hormones and use of energy sources. Hence, it is of prime import...

The current state of artificial intelligence in ophthalmology.

Survey of ophthalmology
Artificial intelligence (AI) is a branch of computer science that deals with the development of algorithms that seek to simulate human intelligence. We provide an overview of the basic principles in AI that are essential to the understanding of AI an...

SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Breast cancer is the second leading cause of cancer death among women worldwide. Nevertheless, it is also one of the most treatable malignances if detected early. Screening for breast cancer with full field digital mammography (FFDM) has been widely ...

Molecular imaging with neural training of identification algorithm (neural network localization identification).

Microscopy research and technique
Superresolution localization microscopy strongly relies on robust identification algorithms for accurate reconstruction of the biological systems it is used to measure. The fields of machine learning and computer vision have provided promising soluti...

Insect-inspired neuromorphic computing.

Current opinion in insect science
The steady improvement in the performance of computing systems seen for many decades is levelling off as the miniaturization of semiconducting technology approaches the atomic limit, facing severe physical and technological issues. Neuromorphic compu...

DGCNN: A convolutional neural network over large-scale labeled graphs.

Neural networks : the official journal of the International Neural Network Society
Exploiting graph-structured data has many real applications in domains including natural language semantics, programming language processing, and malware analysis. A variety of methods has been developed to deal with such data. However, learning grap...

Multiple Mittag-Leffler stability of fractional-order competitive neural networks with Gaussian activation functions.

Neural networks : the official journal of the International Neural Network Society
In this paper, we explore the coexistence and dynamical behaviors of multiple equilibrium points for fractional-order competitive neural networks with Gaussian activation functions. By virtue of the geometrical properties of activation functions, the...

Emergence of Binocular Disparity Selectivity through Hebbian Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Földiák, 1989;...

Organization of the cancer network in SUS: evolution of the care model.

Clinics (Sao Paulo, Brazil)
In the current context of epidemiological transition, demographic changes, changes in consumption and lifestyle habits, and pressure on care costs and organized health systems for acute conditions, the Integrated Care Model by Shortell has become a c...

Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea.

International journal of environmental research and public health
In this study, we design an intelligent model to predict chlorophyll-a concentration, which is the primary indicator of algal blooms, using extreme learning machine (ELM) models. Modeling algal blooms is important for environmental management and eco...