AIMC Topic: Deep Learning
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Reduction of radiation exposure in chest radiography using deep learning-based noise reduction processing: A phantom and retrospective clinical study.
Radiography (London, England : 1995)
Apr 24, 2025
INTRODUCTION: Intelligent noise reduction (INR), a deep learning-based noise reduction developed by Canon, is used in planar radiography to improve image quality and reduce patient exposure dose. This study aimed to evaluate the reduction of patient ...
Exploring the potential and limitations of deep learning and explainable AI for longitudinal life course analysis.
BMC public health
Apr 24, 2025
BACKGROUND: Understanding the complex interplay between life course exposures, such as adverse childhood experiences and environmental factors, and disease risk is essential for developing effective public health interventions. Traditional epidemiolo...
Prediction of significant congenital heart disease in infants and children using continuous wavelet transform and deep convolutional neural network with 12-lead electrocardiogram.
BMC pediatrics
Apr 24, 2025
BACKGROUND: Congenital heart disease (CHD) affects approximately 1% of newborns and is a leading cause of mortality in early childhood. Despite the importance of early detection, current screening methods, such as pulse oximetry and auscultation, hav...
Leveraging TME features and multi-omics data with an advanced deep learning framework for improved Cancer survival prediction.
Scientific reports
Apr 24, 2025
Glioma, a malignant intracranial tumor with high invasiveness and heterogeneity, significantly impacts patient survival. This study integrates multi-omics data to improve prognostic prediction and identify therapeutic targets. Using single-cell data ...
Variational mode directed deep learning framework for breast lesion classification using ultrasound imaging.
Scientific reports
Apr 24, 2025
Breast cancer is the most prevalent cancer and the second cause of cancer related death among women in the United States. Accurate and early detection of breast cancer can reduce the number of mortalities. Recent works explore deep learning technique...
Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN).
Scientific reports
Apr 24, 2025
The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and s...
A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection.
Scientific reports
Apr 24, 2025
Autism Spectrum Disorder (ASD) affects approximately [Formula: see text] of the global population and is characterized by difficulties in social communication and repetitive or obsessive behaviors. Early detection of autism is crucial, as it allows t...
Multimodal representations of transfer learning with snake optimization algorithm on bone marrow cell classification using biomedical histopathological images.
Scientific reports
Apr 24, 2025
Bone marrow (BM) plays a crucial role in the hematopoietic process, producing all of the body's blood cells and maintaining the overall immune and health system. Red and yellow BM are the two various kinds of BM. A comprehensive identification of the...
Comparative analysis of automated foul detection in football using deep learning architectures.
Scientific reports
Apr 24, 2025
Automated foul detection in football represents a challenging task due to the dynamic nature of the game, the variability in player movements, and the ambiguity in differentiating fouls from regular physical contact. This study presents a comprehensi...
Intelligent recognition of human activities using deep learning techniques.
PloS one
Apr 24, 2025
Recognition of Human Actions (HAR) Portrays a crucial significance in various applications due to its ability for analyzing behaviour of humans within videos. This research investigates HAR in Red, Green, and Blue, or RGB videos using frameworks for ...
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