AIMC Topic: Datasets as Topic

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A Novel Fusion Framework Combining Graph Embedding Class-Based Convolutional Recurrent Attention Network with Brown Bear Optimization Algorithm for EEG-Based Parkinson's Disease Recognition.

Journal of molecular neuroscience : MN Mar 15, 2025
Parkinson's disease recognition (PDR) involves identifying Parkinson's disease using clinical evaluations, imaging studies, and biomarkers, focusing on early symptoms like tremors, rigidity, and bradykinesia to facilitate timely treatment. However, d...
Machine Learning Algorithms Parkinson Disease Electroencephalography Datasets as Topic Humans Convolutional Neural Networks
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Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.

Scientific reports Mar 7, 2025
Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor prognosis, especially when it is complicated by the presence of microvascular invasion (MVI). Identifying patients at high risk of MVI is crucial for...
Liver Neoplasms Carcinoma, Hepatocellular Single-Cell Gene Expression Analysis Biomarkers, Tumor Risk Assessment Neoplasm Invasiveness Liver Meta-Analysis as Topic Immunotherapy Gene Expression Regulation, Neoplastic Treatment Outcome Humans Machine Learning Precision Medicine Prognosis Clinical Decision-Making Kaplan-Meier Estimate Mutation Microvessels Datasets as Topic Immune Checkpoint Proteins
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Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

IEEE journal of biomedical and health informatics Mar 6, 2025
Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone mass andsevere resorption in dental implant therapy. To accurately analyze the geometry changesof the bone graft (BG) in the maxillary sinus (MS), it is...
Deep Learning Image Processing, Computer-Assisted Artifacts Maxillary Sinus Maxilla Humans Datasets as Topic Alveolar Ridge Augmentation Postoperative Period Preoperative Period
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Rethinking model prototyping through the MedMNIST+ dataset collection.

Scientific reports Mar 5, 2025
The integration of deep learning based systems in clinical practice is often impeded by challenges rooted in limited and heterogeneous medical datasets. In addition, the field has increasingly prioritized marginal performance gains on a few, narrowly...
Datasets as Topic Humans Neural Networks, Computer Algorithms Databases, Factual Deep Learning Image Processing, Computer-Assisted
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Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.

Sensors (Basel, Switzerland) Feb 28, 2025
BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature of tissue contrasts in the early months of life. The difficulty increases as gray matter (GM) and wh...
White Matter Datasets as Topic Gray Matter Convolutional Neural Networks Infant Image Processing, Computer-Assisted Imaging, Three-Dimensional Humans Spatio-Temporal Analysis Magnetic Resonance Imaging Brain Deep Learning Cerebrospinal Fluid
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FusionNet: Dual input feature fusion network with ensemble based filter feature selection for enhanced brain tumor classification.

Brain research Feb 17, 2025
Brain tumors pose a significant threat to human health, require a precise and quick diagnosis for effective treatment. However, achieving high diagnostic accuracy with traditional methods remains challenging due to the complex nature of brain tumors....
Datasets as Topic Image Processing, Computer-Assisted Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Brain Neoplasms Brain Deep Learning
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Importance of dataset design in developing robust U-Net models for label-free cell morphology evaluation.

Journal of bioscience and bioengineering Feb 10, 2025
Advances in regenerative medicine highlighted the need for label-free cell image analysis to replace conventional microscopic observation for non-invasive cell quality evaluation. Image-based evaluation provides an efficient, quantitative, and automa...
Humans Neural Networks, Computer Animals Image Processing, Computer-Assisted Regenerative Medicine Datasets as Topic Cell Shape
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A Deep Reinforcement Learning-Based Feature Selection Method for Invasive Disease Event Prediction Using Imbalanced Follow-Up Data.

IEEE journal of biomedical and health informatics Feb 10, 2025
The machine learning-based model is a promising paradigm for predicting invasive disease events (iDEs) in breast cancer. Feature selection (FS) is an essential preprocessing technique employed to identify the pertinent features for the prediction mod...
Humans Prognosis Datasets as Topic Female Reinforcement Machine Learning Breast Neoplasms Neoplasm Invasiveness
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Generative and contrastive graph representation learning with message passing.

Neural networks : the official journal of the International Neural Network Society Feb 6, 2025
Self-supervised graph representation learning (SSGRL) has emerged as a promising approach for graph embeddings because it does not rely on manual labels. SSGRL methods are generally divided into generative and contrastive approaches. Generative metho...
Autoencoder Graph Neural Networks Generative Artificial Intelligence Supervised Machine Learning Datasets as Topic
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The Data Artifacts Glossary: a community-based repository for bias on health datasets.

Journal of biomedical science Feb 4, 2025
BACKGROUND: The deployment of Artificial Intelligence (AI) in healthcare has the potential to transform patient care through improved diagnostics, personalized treatment plans, and more efficient resource management. However, the effectiveness and fa...
Humans Artificial Intelligence Bias Datasets as Topic
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