AIMC Topic: Neural Networks, Computer

Clear Filters Showing 23851 to 23860 of 31376 articles

ProLego: tool for extracting and visualizing topological modules in protein structures.

BMC bioinformatics
BACKGROUND: In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection of backbone topology aids in drastically reducing the structure search space. With ProLego, we present a server application to...

Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation.

Physics in medicine and biology
Segmentation of liver in abdominal computed tomography (CT) is an important step for radiation therapy planning of hepatocellular carcinoma. Practically, a fully automatic segmentation of liver remains challenging because of low soft tissue contrast ...

An improved advertising CTR prediction approach based on the fuzzy deep neural network.

PloS one
Combining a deep neural network with fuzzy theory, this paper proposes an advertising click-through rate (CTR) prediction approach based on a fuzzy deep neural network (FDNN). In this approach, fuzzy Gaussian-Bernoulli restricted Boltzmann machine (F...

MRI white matter lesion segmentation using an ensemble of neural networks and overcomplete patch-based voting.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate quantification of white matter hyperintensities (WMH) from Magnetic Resonance Imaging (MRI) is a valuable tool for the analysis of normal brain ageing or neurodegeneration. Reliable automatic extraction of WMH lesions is challenging due to t...

Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine.

Artificial intelligence in medicine
Thalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwide. Under this context, one of the greatest challenges for healthcare professionals is to correctly d...

Technical Note: A deep learning-based autosegmentation of rectal tumors in MR images.

Medical physics
PURPOSE: Manual contouring of gross tumor volumes (GTV) is a crucial and time-consuming process in rectum cancer radiotherapy. This study aims to develop a simple deep learning-based autosegmentation algorithm to segment rectal tumors on T2-weighted ...

Recognition of early stage thigmotaxis in Morris water maze test with convolutional neural network.

PloS one
The Morris water maze test (MWM) is a useful tool to evaluate rodents' spatial learning and memory, but the outcome is susceptible to various experimental conditions. Thigmotaxis is a commonly observed behavioral pattern which is thought to be relate...

Behavioral Learning in a Cognitive Neuromorphic Robot: An Integrative Approach.

IEEE transactions on neural networks and learning systems
We present here a learning system using the iCub humanoid robot and the SpiNNaker neuromorphic chip to solve the real-world task of object-specific attention. Integrating spiking neural networks with robots introduces considerable complexity for ques...

Development of a Robust Algorithm for Detection of Nuclei and Classification of White Blood Cells in Peripheral Blood Smear Images.

Journal of medical systems
Peripheral Blood Smear analysis plays a vital role in diagnosis of many diseases such as leukemia, anemia, malaria, lymphoma and infections. Unusual variations in color, shape and size of blood cells indicate abnormal condition. We used a total of 11...