AIMC Topic: Unsupervised Machine Learning

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Dual-view global and local category-attentive domain alignment for unsupervised conditional adversarial domain adaptation.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2025
Conditional adversarial domain adaptation (CADA) is one of the most commonly used unsupervised domain adaptation (UDA) methods. CADA introduces multimodal information to the adversarial learning process to align the distributions of the labeled sourc...
Algorithms Humans Unsupervised Machine Learning Neural Networks, Computer
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Unsupervised deep learning-based medical image registration: a survey.

Physics in medicine and biology Jan 7, 2025
In recent decades, medical image registration technology has undergone significant development, becoming one of the core technologies in medical image analysis. With the rise of deep learning, deep learning-based medical image registration methods ha...
Image Processing, Computer-Assisted Unsupervised Machine Learning Diagnostic Imaging Humans Deep Learning
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Contrastive Registration for Unsupervised Medical Image Segmentation.

IEEE transactions on neural networks and learning systems Jan 7, 2025
Medical image segmentation is an important task in medical imaging, as it serves as the first step for clinical diagnosis and treatment planning. While major success has been reported using deep learning supervised techniques, they assume a large and...
Neural Networks, Computer Algorithms Humans Image Processing, Computer-Assisted Databases, Factual Unsupervised Machine Learning Deep Learning Diagnostic Imaging
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Unsupervised self-organising map classification of Raman spectra from prostate cell lines uncovers substratified prostate cancer disease states.

Scientific reports Jan 4, 2025
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics ...
Prostate Humans Male Unsupervised Machine Learning Cell Line, Tumor Prostatic Neoplasms Spectrum Analysis, Raman
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Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

Pharmacotherapy Jan 3, 2025
BACKGROUND: Fluid overload (FO) in the intensive care unit (ICU) is common, serious, and may be preventable. Intravenous medications (including administered volume) are a primary cause for FO but are challenging to evaluate as a FO predictor given th...
Humans Water-Electrolyte Imbalance Intensive Care Units Cohort Studies Female Male Unsupervised Machine Learning Aged Machine Learning Middle Aged Retrospective Studies
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Tumor detection on bronchoscopic images by unsupervised learning.

Scientific reports Jan 2, 2025
The diagnosis and early identification of intratracheal tumors relies on the experience of the operators and the specialists. Operations by physicians with insufficient experience may lead to misdiagnosis or misjudgment of tumors. To address this iss...
Humans Image Processing, Computer-Assisted Lung Neoplasms Algorithms Bronchoscopy Unsupervised Machine Learning
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Unsupervised Non-Rigid Histological Image Registration Guided by Keypoint Correspondences Based on Learnable Deep Features With Iterative Training.

IEEE transactions on medical imaging Jan 2, 2025
Histological image registration is a fundamental task in histological image analysis. It is challenging because of substantial appearance differences due to multiple staining. Keypoint correspondences, i.e., matched keypoint pairs, have been introduc...
Image Processing, Computer-Assisted Unsupervised Machine Learning Databases, Factual Deep Learning Humans Algorithms
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OTMorph: Unsupervised Multi-Domain Abdominal Medical Image Registration Using Neural Optimal Transport.

IEEE transactions on medical imaging Jan 2, 2025
Deformable image registration is one of the essential processes in analyzing medical images. In particular, when diagnosing abdominal diseases such as hepatic cancer and lymphoma, multi-domain images scanned from different modalities or different ima...
Unsupervised Machine Learning Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Abdomen Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed
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IGU-Aug: Information-Guided Unsupervised Augmentation and Pixel-Wise Contrastive Learning for Medical Image Analysis.

IEEE transactions on medical imaging Jan 2, 2025
Contrastive learning (CL) is a form of self-supervised learning and has been widely used for various tasks. Different from widely studied instance-level contrastive learning, pixel-wise contrastive learning mainly helps with pixel-wise dense predicti...
Image Processing, Computer-Assisted Unsupervised Machine Learning Humans Algorithms
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Orthogonal Mixed-Effects Modeling for High-Dimensional Longitudinal Data: An Unsupervised Learning Approach.

IEEE transactions on medical imaging Jan 2, 2025
The linear mixed-effects model is commonly utilized to interpret longitudinal data, characterizing both the global longitudinal trajectory across all observations and longitudinal trajectories within individuals. However, characterizing these traject...
Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Longitudinal Studies Unsupervised Machine Learning Magnetic Resonance Imaging Algorithms Female Alzheimer Disease Male Brain
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