AIMC Topic: Neural Networks, Computer

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Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization.

Medical image analysis
Cone-beam computed tomography (CBCT) scans are commonly used in diagnosing and planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities. Based on CBCT images, it is clinically essential to generate an accurate 3D mo...

Dimension independent bounds for general shallow networks.

Neural networks : the official journal of the International Neural Network Society
This paper proves an abstract theorem addressing in a unified manner two important problems in function approximation: avoiding curse of dimensionality and estimating the degree of approximation for out-of-sample extension in manifold learning. We co...

Heartbeat classification using deep residual convolutional neural network from 2-lead electrocardiogram.

Journal of electrocardiology
BACKGROUND: The electrocardiogram (ECG) has been widely used in the diagnosis of heart disease such as arrhythmia due to its simplicity and non-invasive nature. Arrhythmia can be classified into many types, including life-threatening and non-life-thr...

MedGAN: Medical image translation using GANs.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific arc...

Human peripheral blood leukocyte classification method based on convolutional neural network and data augmentation.

Medical physics
PURPOSE: Human peripheral blood leukocytes' classification is important for diagnosing blood diseases. Many microscopic leukocyte image automatic detection methods are proposed. In recent years, convolutional neural networks (CNNs) are applied to mic...

ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network.

EBioMedicine
BACKGROUND: The spatial distributions of different types of cells could reveal a cancer cell's growth pattern, its relationships with the tumor microenvironment and the immune response of the body, all of which represent key "hallmarks of cancer". Ho...

An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network.

Scientific reports
The incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in recent years, and its mortality rate has become one of the highest among all cancers. CRC also increasingly affects people's health and quality of life, and the wor...

ImaGene: a convolutional neural network to quantify natural selection from genomic data.

BMC bioinformatics
BACKGROUND: The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determini...

Analyzing gene expression data for pediatric and adult cancer diagnosis using logic learning machine and standard supervised methods.

BMC bioinformatics
BACKGROUND: Logic Learning Machine (LLM) is an innovative method of supervised analysis capable of constructing models based on simple and intelligible rules. In this investigation the performance of LLM in classifying patients with cancer was evalua...

Memristor-Based Neural Network Circuit of Full-Function Pavlov Associative Memory With Time Delay and Variable Learning Rate.

IEEE transactions on cybernetics
Most memristor-based Pavlov associative memory neural networks strictly require that only simultaneous food and ring appear to generate associative memory. In this article, the time delay is considered, in order to form associative memory when the fo...