AIMC Topic: Neural Networks, Computer

Clear Filters Showing 3731 to 3740 of 31376 articles

A sparse and wide neural network model for DNA sequences.

Neural networks : the official journal of the International Neural Network Society
Accurate modeling of DNA sequences requires capturing distant semantic relationships between the nucleotide acid bases. Most existing deep neural network models face two challenges: (1) they are limited to short DNA fragments and cannot capture long-...

A U-Net based partial convolutional time-domain separation model to identify motor units from surface electromyographic signals in real time.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
This study proposed a U-Net based partial convolutional time-domain model for a real-time high-density surface electromyography (HD-sEMG) decomposition. The model combines U-Net and a separation block containing partial convolution, aiming to efficie...

Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides.

Methods (San Diego, Calif.)
Identifying angiotensin-I-converting enzyme (ACE) inhibitory peptides accurately is crucial for understanding the primary factor that regulates the renin-angiotensin system and for providing guidance in developing new potential drugs. Given the inher...

ECCDN-Net: A deep learning-based technique for efficient organic and recyclable waste classification.

Waste management (New York, N.Y.)
Efficient waste management is essential to minimizing environmental harm as well as encouraging sustainable progress. The escalating volume and sophistication of waste present significant challenges, prompting innovative methods for effective waste c...

Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imaging.

Computers in biology and medicine
We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by exploring manually adjusted versus automated window-setting optimization (WSO)...

A novel case-based reasoning system for explainable lung cancer diagnosis.

Computers in biology and medicine
Lung cancer is a leading cause of cancer death worldwide. The survival rate is generally higher when this disease is detected in its early stages. Advances in artificial intelligence (AI) have enabled the development of decision support systems that ...

Exploring transparency: A comparative analysis of explainable artificial intelligence techniques in retinography images to support the diagnosis of glaucoma.

Computers in biology and medicine
Machine learning models are widely applied across diverse fields, including nearly all segments of human activity. In healthcare, artificial intelligence techniques have revolutionized disease diagnosis, particularly in image classification. Although...

Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.

Computers in biology and medicine
Medical image analysis has significantly benefited from advancements in deep learning, particularly in the application of Generative Adversarial Networks (GANs) for generating realistic and diverse images that can augment training datasets. The commo...

Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties.

Journal of chemical information and modeling
Peptides are crucial in biological processes and therapeutic applications. Given their importance, advancing our ability to predict peptide properties is essential. In this study, we introduce Multi-Peptide, an innovative approach that combines trans...

Use and Comparison of Machine Learning Techniques to Discern the Protein Patterns of Autoantibodies Present in Women with and without Breast Pathology.

Journal of proteome research
Breast cancer (BC) has become a global health problem, ranking first in incidence and fifth in mortality in women around the world. Although there are some diagnostic methods for the disease, these are not sufficiently effective and are invasive. In ...