AIMC Topic: Deep Learning
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Classification of knee osteoarthritis severity using markerless motion capture and long short-term memory fully convolutional network.
Computers in biology and medicine
Jun 28, 2025
This study explored the integration of markerless motion capture and deep learning to classify knee osteoarthritis severity based on gait kinematics, providing an alternative to traditional assessment methods. We employed a Long Short-Term Memory Ful...
DeepEM Playground: Bringing deep learning to electron microscopy labs.
Journal of microscopy
Jun 28, 2025
Deep learning (DL) has transformed image analysis, enabling breakthroughs in segmentation, object detection, and classification. However, a gap persists between cutting-edge DL research and its practical adoption in electron microscopy (EM) labs. Thi...
The diagnostic model from semi-supervised cross modality transformation improved the distinguished ability of X-rays for pulmonary tuberculosis.
Clinical radiology
Jun 27, 2025
BACKGROUND: Early diagnosis of tuberculosis is particularly difficult in resource-poor areas. Traditional chest X-rays (CXR) have limited accuracy, while CT scans are costly and involve radiation exposure. The study aims to improve the diagnostic acc...
D-RD-UNet: A dual-stage dual-class framework with connectivity correction for hepatic vessels segmentation.
Computers in biology and medicine
Jun 27, 2025
Accurate segmentation of hepatic and portal veins is critical for preoperative planning in liver surgery, especially for resection and transplantation procedures. Extensive anatomical variability, pathological alterations, and inherent class imbalanc...
SER inspired deep learning approach to detect cardiac arrhythmias in electrocardiogram signals using Temporal Convolutional Network and graph neural network.
Computers in biology and medicine
Jun 27, 2025
Electrocardiogram (ECG) signals play a critical role in diagnosing cardiovascular diseases (CVDs), yet automated ECG classification remains challenging due to inter-patient variability, signal noise, and heart rhythm complexity. To address these chal...
A comprehensive hybrid model: Combining bioinspired optimization and deep learning for Alzheimer's disease identification.
Computers in biology and medicine
Jun 27, 2025
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive ability and memory function. It is a progressive disease characterized by worsening dementia symptoms over time, starting with mild m...
Artificial Intelligence-Based Detection of Central Retinal Artery Occlusion Within 4.5 Hours on Standard Fundus Photographs.
Journal of the American Heart Association
Jun 27, 2025
BACKGROUND: Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and stroke prevention. However, most stroke centers lack onsite ophthalmic expertise before considering fibrinolytic treatment. This s...
The singing style of female roles in ethnic opera under artificial intelligence and deep neural networks.
Scientific reports
Jun 27, 2025
With the rapid advancement of artificial intelligence technology, efficiently extracting and analyzing music performance style features has become an important topic in the field of music information processing. This work focuses on the classificatio...
Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.
BMJ open respiratory research
Jun 27, 2025
BACKGROUND: Indeterminate pulmonary nodules (IPNs) are commonly biopsied to ascertain a diagnosis of lung cancer, but many are ultimately benign. The Lung Cancer Prediction (LCP) score is a commercially available deep learning radiomic model with str...
ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis.
Journal of medical Internet research
Jun 27, 2025
BACKGROUND: Influenza in mainland China results in a large number of outpatient and emergency visits related to influenza-like illness (ILI) annually. While deep learning models show promise for improving influenza forecasting, their technical comple...
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