This research presents a novel ensemble fuzzy deep learning approach for brain Magnetic Resonance Imaging (MRI) analysis, aiming to improve the segmentation of brain tissues and abnormalities. The method integrates multiple components, including dive...
The limited availability of labeled ECG data restricts the application of supervised deep learning methods in ECG detection. Although existing self-supervised learning approaches have been applied to ECG analysis, they are predominantly image-based, ...
Skin diseases, a significant category in the medical field, have always been challenging to diagnose and have a high misdiagnosis rate. Deep learning for skin disease classification has considerable value in clinical diagnosis and treatment. This stu...
Traffic congestion, particularly in rapidly expanding urban centers, significantly impacts the timely delivery of emergency medical services (EMS), where every minute can mean the difference between life and death. Traditional traffic signal control ...
OBJECTIVES: Artificial Intelligence (AI), particularly deep learning, has significantly impacted healthcare, including dentistry, by improving diagnostics, treatment planning, and prognosis prediction. This systematic mapping review explores the curr...
Biomedical physics & engineering express
Feb 19, 2025
In recent years, deep learning (DL)-based automatic view classification of 2D transthoracic echocardiography (TTE) has demonstrated strong performance, but has not fully addressed key clinical requirements such as view coverage, classification accura...
The integration of Deep Learning (DL) algorithms on brain signal analysis is still in its nascent stages compared to their success in fields like Computer Vision. This is particularly true for Brain-computer interface (BCI), where the brain activity ...
Experimental biology and medicine (Maywood, N.J.)
Feb 19, 2025
Advancements in machine learning and deep learning have the potential to revolutionize the diagnosis of melanocytic choroidal tumors, including uveal melanoma, a potentially life-threatening eye cancer. Traditional machine learning methods rely heavi...
In the field of earth sciences and remote exploration, the classification and identification of surface materials on earth have been a significant research area that poses considerable challenges in recent times. Although deep learning technology has...
OBJECTIVES: Deep learning for body composition analysis (BCA) is gaining traction in clinical research, offering rapid and automated ways to measure body features like muscle or fat volume. However, most current methods prioritize computed tomography...
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