AIMC Journal:
Scientific reports
Showing 691 to 700 of 5345 articles
Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion.
Scientific reports
Mar 14, 2025
Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vigilant. We call this driver sleepiness. This results in numerous unfavourable circumstances that negatively impact people's life. The identification o...
Artificial intelligence-powered prediction of AIM-2 inflammasome sequences using transformers and graph attention networks in periodontal inflammation.
Scientific reports
Mar 13, 2025
Periodontal inflammation is a chronic condition affecting the tissues surrounding teeth. Initiated by dental plaque, it triggers an immune response leading to tissue destruction. The AIM-2 inflammasome regulates this response, and understanding its p...
A multi model deep net with an explainable AI based framework for diabetic retinopathy segmentation and classification.
Scientific reports
Mar 13, 2025
Diabetic Retinopathy (DR) is a serious condition affecting diabetes people caused by hemorrhage in the light-sensitive retinal area. DR sufferers should receive urgent therapy to avoid vision loss. The intelligent medical diagnosis system for DR is e...
Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture.
Scientific reports
Mar 13, 2025
Classifying medical images is essential in computer-aided diagnosis (CAD). Although the recent success of deep learning in the classification tasks has proven advantages over the traditional feature extraction techniques, it remains challenging due t...
A robust deep learning approach for segmenting cortical and trabecular bone from 3D high resolution µCT scans of mouse bone.
Scientific reports
Mar 13, 2025
Recent advancements in deep learning have significantly enhanced the segmentation of high-resolution microcomputed tomography (µCT) bone scans. In this paper, we present the dual-branch attention-based hybrid network (DBAHNet), a deep learning archit...
Machine learning reveals glycolytic key gene in gastric cancer prognosis.
Scientific reports
Mar 13, 2025
Glycolysis is recognized as a central metabolic pathway in the neoplastic evolution of gastric cancer, exerting profound effects on the tumor microenvironment and the neoplastic growth trajectory. However, the identification of key glycolytic genes t...
Developing a seasonal-adjusted machine-learning-based hybrid time‑series model to forecast heatwave warning.
Scientific reports
Mar 13, 2025
Heatwaves pose a significant threat to environmental sustainability and public health, particularly in vulnerable regions and rapidly growing cities. They cause water shortages, stress on plants, and an overall drying out of landscapes, reducing plan...
Development and validation of machine learning-based prediction model for outcome of cardiac arrest in intensive care units.
Scientific reports
Mar 13, 2025
Cardiac arrest (CA) poses a significant global health challenge and often results in poor prognosis. We developed an interpretable and applicable machine learning (ML) model for predicting in-hospital mortality of CA patients who survived more than 7...
Liver margin segmentation in abdominal CT images using U-Net and Detectron2: annotated dataset for deep learning models.
Scientific reports
Mar 13, 2025
The segmentation of liver margins in computed tomography (CT) images presents significant challenges due to the complex anatomical variability of the liver, with critical implications for medical diagnostics and treatment planning. In this study, we ...
ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with interpretable machine learning.
Scientific reports
Mar 13, 2025
Early detection of malignant thyroid nodules is crucial for effective treatment, but traditional diagnostic methods face challenges such as variability in expert opinions and limited integration of advanced imaging techniques. This prospective cohort...
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