AIMC Topic: Supervised Machine Learning

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Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Apr 1, 2025
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...
Supervised Machine Learning Organs at Risk Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Lung Neoplasms Tomography, X-Ray Computed Deep Learning Brachytherapy Humans
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A segment anything model-guided and match-based semi-supervised segmentation framework for medical imaging.

Medical physics Mar 29, 2025
BACKGROUND: Semi-supervised segmentation leverages sparse annotation information to learn rich representations from combined labeled and label-less data for segmentation tasks. The Match-based framework, by using the consistency constraint of segment...
Image Processing, Computer-Assisted Diagnostic Imaging Supervised Machine Learning Humans
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Role of eccentricity based topological descriptors to predict anti-HIV drugs attributes with supervised machine learning algorithms.

Computers in biology and medicine Mar 27, 2025
Chemical graphs are mathematical representations of molecular structures, where atoms are represented as vertices, while chemical bonds are depicted as edges of a graph. The chemical graphs are widely used in cheminformatics to analyze molecular prop...
Drug Design HIV Infections Anti-HIV Agents Machine Learning Algorithms Humans Supervised Machine Learning
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Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey.

BMJ open Mar 22, 2025
OBJECTIVES: This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data.
Logistic Models Bayes Theorem Tanzania Supervised Machine Learning Infant Machine Learning Health Surveys Vaccination Algorithms Cross-Sectional Studies Female Male Humans
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The optimization and impact of public sports service quality based on the supervised learning model and artificial intelligence.

Scientific reports Mar 22, 2025
Aiming at the optimization of public sports service quality, this study analyzes the public sports service data deeply by constructing a supervised learning model. Firstly, the theoretical framework of this study is established. Secondly, the technic...
Humans Supervised Machine Learning Sports Artificial Intelligence Models, Theoretical
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Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound.

Medical image analysis Mar 21, 2025
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, developing an automated system for nodule segmentation can enhance user...
Female Imaging, Three-Dimensional Image Interpretation, Computer-Assisted Humans Supervised Machine Learning Breast Neoplasms Ultrasonography, Mammary Algorithms
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Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning.

PLoS computational biology Mar 17, 2025
Although the cerebellum is typically associated with supervised learning algorithms, it also exhibits extensive involvement in reward processing. In this study, we investigated the cerebellum's role in executing reinforcement learning algorithms, wit...
Purkinje Cells Cerebellum Reward Animals Reinforcement, Psychology Male Mice, Inbred C57BL Supervised Machine Learning Computational Biology Models, Neurological Algorithms Mice
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Masked Deformation Modeling for Volumetric Brain MRI Self-Supervised Pre-Training.

IEEE transactions on medical imaging Mar 17, 2025
Self-supervised learning (SSL) has been proposed to alleviate neural networks' reliance on annotated data and to improve downstream tasks' performance, which has obtained substantial success in several volumetric medical image segmentation tasks. How...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Supervised Machine Learning Adult Male Neuroimaging Humans Brain Female Algorithms
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Effective Semi-Supervised Medical Image Segmentation With Probabilistic Representations and Prototype Learning.

IEEE transactions on medical imaging Mar 17, 2025
Label scarcity, class imbalance and data uncertainty are three primary challenges that are commonly encountered in the semi-supervised medical image segmentation. In this work, we focus on the data uncertainty issue that is overlooked by previous lit...
Algorithms Image Processing, Computer-Assisted Models, Statistical Humans Diagnostic Imaging Supervised Machine Learning
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FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-Supervised Medical Image Segmentation.

IEEE transactions on medical imaging Mar 17, 2025
Federated learning (FL) effectively mitigates the data silo challenge brought about by policies and privacy concerns, implicitly harnessing more data for deep model training. However, traditional centralized FL models grapple with diverse multi-cente...
Image Processing, Computer-Assisted Supervised Machine Learning Algorithms Humans Deep Learning
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