AIMC Topic: Deep Learning

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The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: A preliminary study.

Computers in biology and medicine Jul 1, 2025
Deep learning is significantly advancing the analysis of electroencephalography (EEG) data by effectively discovering highly nonlinear patterns within the signals. Data partitioning and cross-validation are crucial for assessing model performance and...
Electroencephalography Signal Processing, Computer-Assisted Alzheimer Disease Brain-Computer Interfaces Reproducibility of Results Deep Learning Parkinson Disease Humans
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A deep learning model combining convolutional neural networks and a selective kernel mechanism for SSVEP-Based BCIs.

Computers in biology and medicine Jul 1, 2025
Existing deep learning methods for brain-computer interfaces (BCIs) based on steady-state visually evoked potential (SSVEP) face several challenges, such as overfitting when training data are insufficient, and the difficulty of effectively capturing ...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Evoked Potentials, Visual Deep Learning Humans Convolutional Neural Networks Neural Networks, Computer Electroencephalography
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The artificial intelligence challenge in rare disease diagnosis: A case study on collagen VI muscular dystrophy.

Computers in biology and medicine Jul 1, 2025
The use of artificial intelligence (AI) techniques is significantly changing the analysis of medical images, accelerating and standardizing the diagnosis process. To train an AI model, however, a large dataset is typically required, especially when u...
Rare Diseases Humans Muscular Dystrophies Artificial Intelligence Collagen Type VI Deep Learning
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RCFLA-YOLO: a deep learning-driven framework for the automated assessment of root canal filling quality in periapical radiographs.

BMC medical education Jul 1, 2025
BACKGROUND: Evaluating the quality of root canal filling (RCF) performed by dental students in preclinical settings is a time-consuming process for clinicians and is often subjectively assessed.
Students, Dental Clinical Competence Root Canal Obturation Humans Education, Dental Radiography, Dental Deep Learning
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Deep learning-based dipeptidyl peptidase IV inhibitor screening, experimental validation, and GaMD/LiGaMD analysis.

BMC biology Jul 1, 2025
BACKGROUND: Dipeptidyl peptidase-4 (DPP4) is considered a crucial enzyme in type 2 diabetes (T2D) treatment, targeted by inhibitors due to its role in cleaving glucagon-like peptide-1 (GLP-1). In this study, a novel DPP4 inhibitor screening strategy ...
Dipeptidyl Peptidase 4 Humans Dipeptidyl-Peptidase IV Inhibitors Molecular Docking Simulation Molecular Dynamics Simulation Deep Learning Diabetes Mellitus, Type 2 Drug Evaluation, Preclinical Ligands
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Attention-driven hybrid deep learning and SVM model for early Alzheimer's diagnosis using neuroimaging fusion.

BMC medical informatics and decision making Jul 1, 2025
Alzheimer's Disease (AD) poses a significant global health challenge, necessitating early and accurate diagnosis to enable timely interventions. AD is a progressive neurodegenerative disorder that affects millions worldwide and is one of the leading ...
Humans Alzheimer Disease Aged Early Diagnosis Deep Learning Neuroimaging Support Vector Machine
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Preoperative MRI-based deep learning reconstruction and classification model for assessing rectal cancer.

BMC medical imaging Jul 1, 2025
BACKGROUND: To determine whether deep learning reconstruction (DLR) could improve the image quality of rectal MR images, and to explore the discrimination of the TN stage of rectal cancer by different readers and deep learning classification models, ...
Male Middle Aged Deep Learning ROC Curve Signal-To-Noise Ratio Image Processing, Computer-Assisted Diffusion Magnetic Resonance Imaging Magnetic Resonance Imaging Neoplasm Staging Humans Rectal Neoplasms Image Interpretation, Computer-Assisted Retrospective Studies Female Aged Aged, 80 and over Adult
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Deep learning-based automated classification of choroidal layers in en face swept-source optical coherence tomography images.

BMC ophthalmology Jul 1, 2025
BACKGROUND: This study aims to develop a deep learning-based algorithm dedicated to the automated classification of choroidal layers in en face swept-source optical coherence tomography (SS-OCT) images of the eye.
Tomography, Optical Coherence Healthy Volunteers Deep Learning Choroid Algorithms Female Young Adult Adult Male Middle Aged Humans
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women.

BMC medical imaging Jul 1, 2025
BACKGROUND: Current ultrasound-based screening for endometrial cancer (EC) primarily relies on endometrial thickness (ET) and morphological evaluation, which suffer from low specificity and high interobserver variability. This study aimed to develop ...
Endometrium Image Interpretation, Computer-Assisted Postmenopause Middle Aged Deep Learning Ultrasonography Endometrial Neoplasms Neural Networks, Computer Machine Learning Algorithms Female Aged Sensitivity and Specificity Humans
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Enhanced pulmonary nodule detection with U-Net, YOLOv8, and swin transformer.

BMC medical imaging Jul 1, 2025
RATIONALE AND OBJECTIVES: Lung cancer remains the leading cause of cancer-related mortality worldwide, emphasizing the critical need for early pulmonary nodule detection to improve patient outcomes. Current methods encounter challenges in detecting s...
Tomography, X-Ray Computed Deep Learning Lung Neoplasms Humans Algorithms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted
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