AIMC Topic: Deep Learning

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Dynamic Statistical Attention-based lightweight model for Retinal Vessel Segmentation: DyStA-RetNet.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Accurate extraction of retinal vascular components is vital in diagnosing and treating retinal diseases. Achieving precise segmentation of retinal blood vessels is challenging due to their complex structure and overlapping v...

NeuTox 2.0: A hybrid deep learning architecture for screening potential neurotoxicity of chemicals based on multimodal feature fusion.

Environment international
Chemically induced neurotoxicity is a critical aspect of chemical safety assessment. Traditional and costly experimental methods call for the development of high-throughput virtual screening. However, the small datasets of neurotoxicity have limited ...

Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.

Scientific reports
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breas...

Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.

Scientific reports
Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and miti...

Conceptual understanding and cognitive patterns construction for physical education teaching based on deep learning algorithms.

Scientific reports
To improve students' understanding of physical education teaching concepts and help teachers analyze students' cognitive patterns, the study proposes an association learning-based method for understanding physical education teaching concepts using de...

Quality prediction of air-cured cigar tobacco leaf using region-based neural networks combined with visible and near-infrared hyperspectral imaging.

Scientific reports
Visible and Near-infrared hyperspectral imaging (VNIR-HSI) combined with machine learning has shown its effectiveness in various detection applications. Specifically, the quality of cigar tobacco leaves undergoes subtle changes due to environmental d...

Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells.

Scientific reports
Double negative T (DNT) cells are a unique subset of CD3 + TCRαβ + T lymphocytes that lack CD4, CD8, or NK1.1 expression and constitute 3-5% of the total T cell population in C57BL/6 mice. They have increasingly gained recognition for their novel rol...

Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.

BMC genomics
Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions with proteins. Accurate identification of lncRNA-protein interactions (LPI) can help elucidate the func...

A new prediction model based on deep learning for pig house environment.

Scientific reports
A prediction model of the pig house environment based on Bayesian optimization (BO), squeeze and excitation block (SE), convolutional neural network (CNN) and gated recurrent unit (GRU) is proposed to improve the prediction accuracy and animal welfar...

CDUNeXt: efficient ossification segmentation with large kernel and dual cross gate attention.

Scientific reports
Ossification of the ligamentum flavum (OLF) is the main causative factor of spinal stenosis, but how to accurately and efficiently identify the ossification region is a clinical pain point and an urgent problem to be solved. Currently, we can only re...