AIMC Topic: Humans

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Unsupervised Cross-Modality Domain Adaptation Network for X-Ray to CT Registration.

IEEE journal of biomedical and health informatics
2D/3D registration that achieves high accuracy and real-time computation is one of the enabling technologies for radiotherapy and image-guided surgeries. Recently, the Convolutional Neural Network (CNN) has been explored to significantly improve the ...

Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review.

Frontiers in public health
Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed ...

The Design of Psychological Education Intervention System in Universities Based on Deep Learning.

Computational intelligence and neuroscience
With the rapid development of Chinese society and economy as well as the deepening of the reform of the higher education management system and the change of employment mode of graduates, college students face various challenges of frustration and pre...

An Animation Model Generation Method Based on Gaussian Mutation Genetic Algorithm to Optimize Neural Network.

Computational intelligence and neuroscience
With the rapid development of computer graphics, 3D animation has been applied to all fields of people's lives, especially in the industries of film and television works, games, and entertainment. The wide application of animation technology makes it...

Insights into the relationship between usability and willingness to use a robot in the future workplaces: Studying the mediating role of trust and the moderating roles of age and STARA.

PloS one
BACKGROUND AND AIM: Human-robot collaboration is the key component of the fourth industrial revolution concept. Workers' willingness to collaborate with industrial robots is a basic requirement for an efficient and effective interaction. The roles of...

DiaDeL: An Accurate Deep Learning-Based Model With Mutational Signatures for Predicting Metastasis Stage and Cancer Types.

IEEE/ACM transactions on computational biology and bioinformatics
Mutational signatures help identify cancer-associated genes that are being involved in tumorigenesis pathways. Hence, these pathways guide precision medicine approaches to find appropriate drugs and treatments. The pattern of mutations varies in diff...

Genetic Analysis of Coronary Artery Disease Using Tree-Based Automated Machine Learning Informed By Biology-Based Feature Selection.

IEEE/ACM transactions on computational biology and bioinformatics
Machine Learning (ML) approaches are increasingly being used in biomedical applications. Important challenges of ML include choosing the right algorithm and tuning the parameters for optimal performance. Automated ML (AutoML) methods, such as Tree-ba...

Heterogeneity in Blood Biomarker Trajectories After Mild TBI Revealed by Unsupervised Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Concussions, also known as mild traumatic brain injury (mTBI), are a growing health challenge. Approximately four million concussions are diagnosed annually in the United States. Concussion is a heterogeneous disorder in causation, symptoms, and outc...

EPGAT: Gene Essentiality Prediction With Graph Attention Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying essential genes and proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches helped to mitigate experimental constraints by exploring machine learning (ML) methods and the correla...

RNN-VirSeeker: A Deep Learning Method for Identification of Short Viral Sequences From Metagenomes.

IEEE/ACM transactions on computational biology and bioinformatics
Viruses are the most abundant biological entities on earth, and play vital roles in many aspects of microbial communities. As major human pathogens, viruses have caused huge mortality and morbidity to human society in history. Metagenomic sequencing ...