AIMC Topic: Neural Networks, Computer

Clear Filters Showing 17611 to 17620 of 31376 articles

Convolutional neural networks with image representation of amino acid sequences for protein function prediction.

Computational biology and chemistry
Proteins are one of the most important molecules that govern the cellular processes in most of the living organisms. Various functions of the proteins are of paramount importance to understand the basics of life. Several supervised learning approache...

Diagnosis of Leukaemia in Blood Slides Based on a Fine-Tuned and Highly Generalisable Deep Learning Model.

Sensors (Basel, Switzerland)
Leukaemia is a dysfunction that affects the production of white blood cells in the bone marrow. Young cells are abnormally produced, replacing normal blood cells. Consequently, the person suffers problems in transporting oxygen and in fighting infect...

Application of Supervised SOM Algorithms in Predicting the Hepatotoxic Potential of Drugs.

International journal of molecular sciences
The hepatotoxic potential of drugs is one of the main reasons why a number of drugs never reach the market or have to be withdrawn from the market. Therefore, the evaluation of the hepatotoxic potential of drugs is an important part of the drug devel...

Machine learning to reveal an astute risk predictive framework for Gynecologic Cancer and its impact on women psychology: Bangladeshi perspective.

BMC bioinformatics
BACKGROUND: In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress.

KecNet: A Light Neural Network for Arrhythmia Classification Based on Knowledge Reinforcement.

Journal of healthcare engineering
Acquiring electrocardiographic (ECG) signals and performing arrhythmia classification in mobile device scenarios have the advantages of short response time, almost no network bandwidth consumption, and human resource savings. In recent years, deep ne...

Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Computational and mathematical methods in medicine
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...

Incorporation of residual attention modules into two neural networks for low-dose CT denoising.

Medical physics
PURPOSE: The low-dose computed tomography (CT) imaging can reduce the damage caused by x-ray radiation to the human body. However, low-dose CT images have a different degree of artifacts than conventional CT images, and their resolution is lower than...

Contextual embedding bootstrapped neural network for medical information extraction of coronary artery disease records.

Medical & biological engineering & computing
Coronary artery disease (CAD) is the major cause of human death worldwide. The development of new CAD early diagnosis methods based on medical big data has a great potential to reduce the risk of CAD death. In this process, neural network (NN), as a ...

3D MRI Reconstruction Based on 2D Generative Adversarial Network Super-Resolution.

Sensors (Basel, Switzerland)
The diagnosis of brain pathologies usually involves imaging to analyze the condition of the brain. Magnetic resonance imaging (MRI) technology is widely used in brain disorder diagnosis. The image quality of MRI depends on the magnetostatic field str...

Deep Learning in Virtual Screening: Recent Applications and Developments.

International journal of molecular sciences
Drug discovery is a cost and time-intensive process that is often assisted by computational methods, such as virtual screening, to speed up and guide the design of new compounds. For many years, machine learning methods have been successfully applied...