AIMC Topic: Unsupervised Machine Learning

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Unsupervised learning reveals rapid gait adaptation after leg loss and regrowth in spiders.

The Journal of experimental biology Jun 17, 2025
Many invertebrates voluntarily lose (autotomize) limbs during antagonistic encounters, and some regenerate functional replacements. Because limb loss can have severe consequences on individual fitness, it is likely subject to significant selective pr...
Animals Unsupervised Machine Learning Gait Biomechanical Phenomena Extremities Adaptation, Physiological Spiders Regeneration Video Recording Locomotion
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Unsupervised learning-based quantitative analysis of CT intratumoral subregions predicts risk stratification of bladder cancer patients.

BMC medicine Jun 2, 2025
BACKGROUND: Preoperative diagnosis of muscle invasion and American Joint Committee on Cancer (AJCC) stage plays a crucial role in guiding treatment strategies for bladder cancer (BCa). Utilizing quantitative analysis of tumor subregions via CT imagin...
Tomography, X-Ray Computed Female Aged Humans Retrospective Studies Urinary Bladder Neoplasms Unsupervised Machine Learning Neoplasm Staging Male Middle Aged Risk Assessment
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Dynamic Multi-scale Feature Integration Network for unsupervised MR-CT synthesis.

Neural networks : the official journal of the International Neural Network Society May 21, 2025
Unsupervised MR-CT synthesis presents a significant opportunity to reduce radiation exposure from CT scans and lower costs by eliminating the need for both MR and CT imaging. However, many existing unsupervised methods face limitations in capturing d...
Humans Magnetic Resonance Imaging Unsupervised Machine Learning Neural Networks, Computer Brain Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Unsupervised feature selection with evolutionary sparsity.

Neural networks : the official journal of the International Neural Network Society May 7, 2025
The ℓ-norm is playing an increasingly important role in unsupervised feature selection. However, existing algorithm for optimization problem with ℓ-norm constraint has two problems: First, they cannot automatically determine the sparsity, also known ...
Algorithms Unsupervised Machine Learning Humans Biological Evolution Neural Networks, Computer
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Unsupervised Test-Time Adaptation for Hepatic Steatosis Grading Using Ultrasound B-Mode Images.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control May 7, 2025
Ultrasound (US) is considered a key modality for the clinical assessment of hepatic steatosis (i.e., fatty liver) due to its noninvasiveness and availability. Deep learning methods have attracted considerable interest in this field, as they are capab...
Middle Aged Deep Learning Ultrasonography Image Interpretation, Computer-Assisted Fatty Liver Humans Female Neural Networks, Computer Liver Male Algorithms Unsupervised Machine Learning
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Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition.

IEEE journal of biomedical and health informatics May 6, 2025
Robust decoding performance is essential for the practical deployment of brain-computer interface (BCI) systems. Existing EEG decoding models often rely on large amounts of annotated data collected through specific experimental setups, which fail to ...
Humans Algorithms Electroencephalography Signal Processing, Computer-Assisted Adult Imagination Female Brain-Computer Interfaces Male Young Adult Unsupervised Machine Learning
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Feedback Attention to Enhance Unsupervised Deep Learning Image Registration in 3D Echocardiography.

IEEE transactions on medical imaging May 2, 2025
Cardiac motion estimation is important for assessing the contractile health of the heart, and performing this in 3D can provide advantages due to the complex 3D geometry and motions of the heart. Deep learning image registration (DLIR) is a robust wa...
Humans Algorithms Unsupervised Machine Learning Heart Female Echocardiography, Three-Dimensional Adult Deep Learning
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Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction.

IEEE transactions on medical imaging May 2, 2025
Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. However, the requirement of excessive high-quality ground-truth data hi...
Unsupervised Machine Learning Heart Humans Neural Networks, Computer Algorithms Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Unsupervised Domain Adaptation for Low-Dose CT Reconstruction via Bayesian Uncertainty Alignment.

IEEE transactions on neural networks and learning systems May 2, 2025
Low-dose computed tomography (LDCT) image reconstruction techniques can reduce patient radiation exposure while maintaining acceptable imaging quality. Deep learning (DL) is widely used in this problem, but the performance of testing data (also known...
Deep Learning Image Processing, Computer-Assisted Unsupervised Machine Learning Bayes Theorem Radiation Dosage Uncertainty Humans Algorithms Tomography, X-Ray Computed
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Supervised and unsupervised learning reveal heroin-induced impairments in astrocyte structural plasticity.

Science advances Apr 30, 2025
Astrocytes regulate synaptic activity across large brain territories via their complex, interconnected morphology. Emerging evidence supports the involvement of astrocytes in shaping relapse to opioid use through morphological rearrangements in the n...
Supervised Machine Learning Neuronal Plasticity Animals Nucleus Accumbens Unsupervised Machine Learning Male Heroin Astrocytes
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