AIMC Topic: Supervised Machine Learning

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An efficient framework based on local multi-representatives and noise-robust synthetic example generation for self-labeled semi-supervised classification.

Neural networks : the official journal of the International Neural Network Society Jan 16, 2025
While self-labeled methods can exploit unlabeled and labeled instances to train classifiers, they are also restricted by the labeled instance number and distribution. SEG-SSC, k-means-SSC, LC-SSC, and LCSEG-SSC are sophisticated solutions for overcom...
Pattern Recognition, Automated Neural Networks, Computer Algorithms Humans Cluster Analysis Supervised Machine Learning
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Simplified self-supervised learning for hybrid propagation graph-based recommendation.

Neural networks : the official journal of the International Neural Network Society Jan 16, 2025
Recent progress in Graph Convolutional Networks (GCNs) has facilitated their extensive application in recommendation, yielding notable performance gains. Nevertheless, existing GCN-based recommendation approaches are confronted with several challenge...
Humans Neural Networks, Computer Algorithms Supervised Machine Learning
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Supervised Contrastive Learning-Based Domain Generalization Network for Cross-Subject Motor Decoding.

IEEE transactions on bio-medical engineering Jan 15, 2025
Developing an electroencephalogram (EEG)-based motor imagery and motor execution (MI/ME) decoding system that is both highly accurate and calibration-free for cross-subject applications remains challenging due to domain shift problem inherent in such...
Humans Algorithms Electroencephalography Signal Processing, Computer-Assisted Supervised Machine Learning Adult Male
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Weakly-supervised thyroid ultrasound segmentation: Leveraging multi-scale consistency, contextual features, and bounding box supervision for accurate target delineation.

Computers in biology and medicine Jan 13, 2025
Weakly-supervised learning (WSL) methods have gained significant attention in medical image segmentation, but they often face challenges in accurately delineating boundaries due to overfitting to weak annotations such as bounding boxes. This issue is...
Thyroid Gland Ultrasonography Supervised Machine Learning Image Processing, Computer-Assisted Humans Algorithms
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Using supervised machine learning and ICD10 to identify non-accidental trauma in pediatric trauma patients in the Maryland Health Services Cost Review Commission dataset.

Child abuse & neglect Jan 11, 2025
BACKGROUND: Identifying non-accidental trauma (NAT) in pediatric trauma patients is challenging. We developed a machine learning model that uses demographic characteristics and ICD10 codes to detect the first diagnosis of NAT.
Maryland Child Abuse Child, Preschool Child International Classification of Diseases Wounds and Injuries Supervised Machine Learning Infant Humans Adolescent Young Adult Female Male Infant, Newborn Machine Learning
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Semi-Supervised Learning Allows for Improved Segmentation With Reduced Annotations of Brain Metastases Using Multicenter MRI Data.

Journal of magnetic resonance imaging : JMRI Jan 10, 2025
BACKGROUND: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation ...
Humans Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Supervised Machine Learning Brain Neoplasms Male Deep Learning Retrospective Studies Middle Aged Image Processing, Computer-Assisted Algorithms Female Brain Reproducibility of Results
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The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden.

The American journal of pathology Jan 10, 2025
Colorectal cancer (CRC) is one of the top three most lethal malignancies worldwide, posing a significant threat to human health. Recently proposed immunotherapy checkpoint blockade treatments have proven effective for CRC, but their use depends on me...
Humans Multiple-Instance Learning Algorithms ROC Curve Colorectal Neoplasms Biomarkers, Tumor Mutation Supervised Machine Learning
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DP-CLAM: A weakly supervised benign-malignant classification study based on dual-angle scanning ultrasound images of thyroid nodules.

Medical engineering & physics Jan 10, 2025
In this paper, a two-stage task weakly supervised learning algorithm is proposed. It accurately achieved patient-level classification task of benign and malignant thyroid nodules based on ultrasound images from two scanning angles: long axis and shor...
Ultrasonography Image Processing, Computer-Assisted Humans Thyroid Nodule Supervised Machine Learning Algorithms
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A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment.

PloS one Jan 10, 2025
In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performanc...
Humans Algorithms Risk Assessment Unsupervised Machine Learning Supervised Machine Learning Support Vector Machine Cluster Analysis
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Disentangled Active Learning on Graphs.

Neural networks : the official journal of the International Neural Network Society Jan 9, 2025
Active learning on graphs (ALG) has emerged as a compelling research field due to its capacity to address the challenge of label scarcity. Existing ALG methods incorporate diversity into their query strategies to maximize the gains from node sampling...
Supervised Machine Learning Humans Computer Graphics Neural Networks, Computer Algorithms
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