AIMC Topic: Neural Networks, Computer

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Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer.

World journal of gastroenterology
BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate. Early prognosis of esophageal abnormalities can improve patient survival rates. The progression of esophageal cancer follows a sequence from esophagi...

GNNs and ensemble models enhance the prediction of new sRNA-mRNA interactions in unseen conditions.

BMC bioinformatics
Bacterial small RNAs (sRNAs) are pivotal in post-transcriptional regulation, affecting functions like virulence, metabolism, and gene expression by binding specific mRNA targets. Identifying these targets is crucial to understanding sRNA regulation a...

Towards precision agriculture tea leaf disease detection using CNNs and image processing.

Scientific reports
In this study, we introduce a groundbreaking deep learning (DL) model designed for the precise task of classifying common diseases in tea leaves, leveraging advanced image analysis techniques. Our model is distinguished by its complex multi-layer arc...

An automated deep learning framework for brain tumor classification using MRI imagery.

Scientific reports
The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment strategies for each ...

Unsupervised post-training learning in spiking neural networks.

Scientific reports
The human brain is a dynamic system that is constantly learning. It employs a combination of various learning strategies to facilitate complex learning processes. However, implementing biological learning mechanisms into Spiking Neural Networks (SNNs...

Deep learning classification integrating embryo images with associated clinical information from ART cycles.

Scientific reports
An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enabling accurate prediction of clinical pregnancy outcomes in single embryo transfer procedures. Three ...

Integrating machine learning and traditional methods for cadmium prediction and bioavailability assessment in Paeoniae Radix Alba: a case study from Bozhou, Anhui Province.

Environmental geochemistry and health
Soil heavy metal contamination, particularly cadmium (Cd), poses a significant risk to ecosystems and human health. This study investigates the distribution and bioavailability of Cd in soil and Paeoniae Radix Alba system from Qiaocheng District, Boz...

MRI-based diagnostic model for Alzheimer's disease using 3D-ResNet.

Biomedical physics & engineering express
Alzheimer's disease (AD), a progressive neurodegenerative disorder, is the leading cause of dementia worldwide and remains incurable once it begins. Therefore, early and accurate diagnosis is essential for effective intervention. Leveraging recent ad...

Driver Steering Intention Prediction for Human-Machine Shared Systems of Intelligent Vehicles Based on CNN-GRU Network.

Sensors (Basel, Switzerland)
In order to mitigate human-machine conflicts and optimize shared control strategy in advance, it is essential for the shared control system to understand and predict driver behavior. This paper proposes a method for predicting driver steering intenti...

[AConvLSTM U-Net: a multi-scale jaw cyst segmentation model based on bidirectional dense connection and attention mechanism].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVES: We propose a multi-scale jaw cyst segmentation model, AConvLSTM U-Net, which is based on bidirectional dense connections and attention mechanisms to achieve accurate automatic segmentation of mandibular cyst images.