AIMC Topic: Algorithms

Clear Filters Showing 10841 to 10850 of 28713 articles

Graph neural network-based cell switching for energy optimization in ultra-dense heterogeneous networks.

Scientific reports
The development of ultra-dense heterogeneous networks (HetNets) will cause a significant rise in energy consumption with large-scale base station (BS) deployments, requiring cellular networks to be more energy efficient to reduce operational expense ...

Merging enzymatic and synthetic chemistry with computational synthesis planning.

Nature communications
Synthesis planning programs trained on chemical reaction data can design efficient routes to new molecules of interest, but are limited in their ability to leverage rare chemical transformations. This challenge is acute for enzymatic reactions, which...

Feedback-AVPGAN: Feedback-guided generative adversarial network for generating antiviral peptides.

Journal of bioinformatics and computational biology
In this study, we propose , a system that aims to computationally generate novel antiviral peptides (AVPs). This system relies on the key premise of the Generative Adversarial Network (GAN) model and the Feedback method. GAN, a generative modeling ap...

Handover Optimization Algorithm Based on T2RFS-FNN.

Computational intelligence and neuroscience
As a key technology for highly reliable communication in the fifth generation mobile communication for railway (5G-R) high-speed railway wireless communication system, once the handover fails, it will pose a serious risk to the safe operation of high...

Predicting adverse drug effects: A heterogeneous graph convolution network with a multi-layer perceptron approach.

PloS one
We apply a heterogeneous graph convolution network (GCN) combined with a multi-layer perceptron (MLP) denoted by GCNMLP to explore the potential side effects of drugs. Here the SIDER, OFFSIDERS, and FAERS are used as the datasets. We integrate the dr...

Iterative Reconstruction: State-of-the-Art and Future Perspectives.

Journal of computer assisted tomography
Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented vari...

Opportunities and Challenges with Artificial Intelligence in Genomics.

Clinics in laboratory medicine
The development of artificial intelligence and machine learning algorithms may allow for advances in patient care. There are existing and potential applications in cancer diagnosis and monitoring, identification of at-risk groups of individuals, clas...

Artificial Intelligence in the Clinical Laboratory: An Overview with Frequently Asked Questions.

Clinics in laboratory medicine
This article provides an overview of machine learning fundamentals and some applications of machine learning to clinical laboratory diagnostics and patient management. A key goal of this article is to provide a basic foundation in clinical machine le...

Accuracy of a Deep Learning Method for Heart Sound Analysis is Unrealistic.

Neural networks : the official journal of the International Neural Network Society

Heart disease prediction using IoT based framework and improved deep learning approach: Medical application.

Medical engineering & physics
Heart disease is the biggest cause of death in the globe. The method of predicting cardiac disease is exceedingly complex. It can only be done properly if the doctor has a lot of expertise and is well-versed in the condition. IoT-based illness predic...