AIMC Topic: Neural Networks, Computer

Clear Filters Showing 27911 to 27920 of 31376 articles

Interpreting generative adversarial networks to infer natural selection from genetic data.

Genetics
Understanding natural selection and other forms of non-neutrality is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent...

Meta predictive learning model of languages in neural circuits.

Physical review. E
Large language models based on self-attention mechanisms have achieved astonishing performances, not only in natural language itself, but also in a variety of tasks of different nature. However, regarding processing language, our human brain may not ...

Machine learning and new insights for breast cancer diagnosis.

The Journal of international medical research
Breast cancer (BC) is the most prominent form of cancer among females all over the world. The current methods of BC detection include X-ray mammography, ultrasound, computed tomography, magnetic resonance imaging, positron emission tomography and bre...

A robust balancing mechanism for spiking neural networks.

Chaos (Woodbury, N.Y.)
Dynamical balance of excitation and inhibition is usually invoked to explain the irregular low firing activity observed in the cortex. We propose a robust nonlinear balancing mechanism for a random network of spiking neurons, which works also in the ...

Influence of training and expertise on deep neural network attention and human attention during a medical image classification task.

Journal of vision
In many different domains, experts can make complex decisions after glancing very briefly at an image. However, the perceptual mechanisms underlying expert performance are still largely unknown. Recently, several machine learning algorithms have been...

Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Hair and scalp disorders present a significant challenge in dermatology due to their clinical diversity and overlapping symptoms, often leading to misdiagnoses. Traditional diagnostic methods rely heavily on clinical expertise and are lim...

NGCN: Drug-target interaction prediction by integrating information and feature learning from heterogeneous network.

Journal of cellular and molecular medicine
Drug-target interaction (DTI) prediction is essential for new drug design and development. Constructing heterogeneous network based on diverse information about drugs, proteins and diseases provides new opportunities for DTI prediction. However, the ...

Hi-GeoMVP: a hierarchical geometry-enhanced deep learning model for drug response prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Personalized cancer treatments require accurate drug response predictions. Existing deep learning methods show promise but higher accuracy is needed to serve the purpose of precision medicine. The prediction accuracy can be improved with ...

Coding genomes with gapped pattern graph convolutional network.

Bioinformatics (Oxford, England)
MOTIVATION: Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network-based methods can be prime candidates for retrieving insights from these sequences because of their applicability to large and diverse datasets. Howe...

Contrastive pre-training and 3D convolution neural network for RNA and small molecule binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: The diverse structures and functions inherent in RNAs present a wealth of potential drug targets. Some small molecules are anticipated to serve as leading compounds, providing guidance for the development of novel RNA-targeted therapeutic...