AIMC Topic: Deep Learning
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Deep learning-based lung cancer classification of CT images.
BMC cancer
Jul 1, 2025
Lung cancer remains a leading cause of cancer-related deaths worldwide, with accurate classification of lung nodules being critical for early diagnosis. Traditional radiological methods often struggle with high false-positive rates, underscoring the ...
Eff-ReLU-Net: a deep learning framework for multiclass wound classification.
BMC medical imaging
Jul 1, 2025
Chronic wounds have emerged as a significant medical challenge due to their adverse effects, including infections leading to amputations. Over the past few years, the prevalence of chronic wounds has grown, thus posing significant health hazards. It ...
Accelerating brain T2-weighted imaging using artificial intelligence-assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI.
BMC medical imaging
Jul 1, 2025
BACKGROUND: T2-weighted imaging (T2WI), renowned for its sensitivity to edema and lesions, faces clinical limitations due to prolonged scanning time, increasing patient discomfort, and motion artifacts. The individual applications of artificial intel...
Multimodal deep learning-based radiomics for meningioma consistency prediction: integrating T1 and T2 MRI in a multi-center study.
BMC medical imaging
Jul 1, 2025
BACKGROUND: Meningioma consistency critically impacts surgical planning, as soft tumors are easier to resect than hard tumors. Current assessments of tumor consistency using MRI are subjective and lack quantitative accuracy. Integrating deep learning...
Muscle-Driven prognostication in gastric cancer: A multicenter deep learning framework integrating Iliopsoas and erector spinae radiomics for 5-Year survival prediction.
Scientific reports
Jul 1, 2025
This study developed a 5-year survival prediction model for gastric cancer patients by combining radiomics and deep learning, focusing on CT-based 2D and 3D features of the iliopsoas and erector spinae muscles. Retrospective data from 705 patients ac...
Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.
Scientific reports
Jul 1, 2025
Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal clinical records. The motivation stems from the need for timely medical resource allocation, improved ...
Determination of the oral carcinoma and sarcoma in contrast enhanced CT images using deep convolutional neural networks.
Scientific reports
Jul 1, 2025
Oral cancer is a hazardous disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop the deep convolutional neural networks (CNN)-based multiclass classification and object detection models for distingui...
Multiscale wavelet attention convolutional network for facial expression recognition.
Scientific reports
Jul 1, 2025
Deep learning techniques, particularly Convolutional Neural Networks (CNNs), have been widely recognized as effective tools for facial expression recognition applications. The accuracy of facial expression recognition application requires further enh...
A hybrid XAI-driven deep learning framework for robust GI tract disease diagnosis.
Scientific reports
Jul 1, 2025
The stomach is one of the main digestive organs in the GIT, essential for digestion and nutrient absorption. However, various gastrointestinal diseases, including gastritis, ulcers, and cancer, affect health and quality of life severely. The precise ...
Development and evaluation of an automated classification and counting system for rice planthoppers captured on survey boards.
Scientific reports
Jul 1, 2025
Rice planthoppers are the most economically important insect pests of rice in Asia. Traditional surveys to examine their abundance and composition in paddy fields involve human visual inspection, which requires considerable time and effort by expert ...
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