AIMC Topic: Neural Networks, Computer

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Artificial Intelligence Radiotherapy Planning: Automatic Segmentation of Human Organs in CT Images Based on a Modified Convolutional Neural Network.

Frontiers in public health
OBJECTIVE: Precise segmentation of human organs and anatomic structures (especially organs at risk, OARs) is the basis and prerequisite for the treatment planning of radiation therapy. In order to ensure rapid and accurate design of radiotherapy trea...

Detection and Classification of Colorectal Polyp Using Deep Learning.

BioMed research international
Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required to save the life of patients. Cancer grows from polyps which can be either cancerous or noncancerous...

U-Net-Based Medical Image Segmentation.

Journal of healthcare engineering
Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the perfo...

A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.

Computational intelligence and neuroscience
An active research area where the experts from the medical field are trying to envisage the problem with more accuracy is diabetes prediction. Surveys conducted by WHO have shown a remarkable increase in the diabetic patients. Diabetes generally rema...

Prediction of Purchase Volume of Cross-Border e-Commerce Platform Based on BP Neural Network.

Computational intelligence and neuroscience
As a new form of foreign trade, cross-border e-commerce has huge development potential. Although the development prospect of cross-border e-commerce is good, the management of global supply chain is very important in order to gain a place in the fier...

Diagnosis of Retinal Diseases Based on Bayesian Optimization Deep Learning Network Using Optical Coherence Tomography Images.

Computational intelligence and neuroscience
Retinal abnormalities have emerged as a serious public health concern in recent years and can manifest gradually and without warning. These diseases can affect any part of the retina, causing vision impairment and indeed blindness in extreme cases. T...

Intelligent Recognition Model of Business English Translation Based on Improved GLR Algorithm.

Computational intelligence and neuroscience
Aiming at the problem of low accuracy of traditional algorithm model, an intelligent recognition model of business English translation based on an improved GLR algorithm is proposed. Through this algorithm, the automatic sentence recognition technolo...

A Convolutional Neural Network-Based Model for Supply Chain Financial Risk Early Warning.

Computational intelligence and neuroscience
At present, there are widespread financing difficulties in China's trade circulation industry. Supply chain finance can provide financing for small- and medium-sized enterprises in China's trade circulation industry, but it will produce financing ris...

WalkIm: Compact image-based encoding for high-performance classification of biological sequences using simple tuning-free CNNs.

PloS one
The classification of biological sequences is an open issue for a variety of data sets, such as viral and metagenomics sequences. Therefore, many studies utilize neural network tools, as the well-known methods in this field, and focus on designing cu...

Comparison of machine learning approaches for radioisotope identification using NaI(TI) gamma-ray spectrum.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
This research aims at comparing the performance of different machine learning algorithms used for NaI(TI) gamma-ray detector based radioisotope identification. Six machine learning algorithms were implemented, including support vector machine (SVM), ...