AIMC Topic: Unsupervised Machine Learning

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Unlocking the soundscape of coral reefs with artificial intelligence: pretrained networks and unsupervised learning win out.

PLoS computational biology Apr 28, 2025
Passive acoustic monitoring can offer insights into the state of coral reef ecosystems at low-costs and over extended temporal periods. Comparison of whole soundscape properties can rapidly deliver broad insights from acoustic data, in contrast to de...
Fishes Neural Networks, Computer Coral Reefs Environmental Monitoring Animals Artificial Intelligence Ecosystem Unsupervised Machine Learning Computational Biology Machine Learning Acoustics Algorithms
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Identification of Risk Group for Root Caries and Analysis of Associated Factors in Older Adults Using Unsupervised Machine Learning Clustering.

Clinical interventions in aging Apr 24, 2025
PURPOSE: This study aimed to identify the high-risk group for root caries using unsupervised machine learning and to explore the associated factors.
Root Caries Risk Assessment Aged Age Factors Cross-Sectional Studies ROC Curve Humans Cluster Analysis Female Logistic Models Male Unsupervised Machine Learning Risk Factors
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Unsupervised non-small cell lung cancer tumor segmentation using cycled generative adversarial network with similarity-based discriminator.

Journal of applied clinical medical physics Apr 23, 2025
BACKGROUND: Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods rely on manually annotated data for network training.
Humans Neural Networks, Computer Image Processing, Computer-Assisted Lung Neoplasms Carcinoma, Non-Small-Cell Lung Algorithms Tomography, X-Ray Computed Deep Learning Unsupervised Machine Learning Generative Adversarial Networks
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SynMSE: A multimodal similarity evaluator for complex distribution discrepancy in unsupervised deformable multimodal medical image registration.

Medical image analysis Apr 22, 2025
Unsupervised deformable multimodal medical image registration often confronts complex scenarios, which include intermodality domain gaps, multi-organ anatomical heterogeneity, and physiological motion variability. These factors introduce substantial ...
Unsupervised Machine Learning Humans Multimodal Imaging Algorithms Tomography, X-Ray Computed Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Brain Magnetic Resonance Imaging
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Deconvolution of cell types and states in spatial multiomics utilizing TACIT.

Nature communications Apr 21, 2025
Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning increasingly plays a role, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in...
Brain Unsupervised Machine Learning Transcriptome Humans Deep Learning Multiomics Animals Mice Gene Expression Profiling Intestines Proteomics
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Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.

Scientific reports Apr 18, 2025
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
Tomography, Optical Coherence Macular Edema Vascular Endothelial Growth Factor A Unsupervised Machine Learning Visual Acuity Principal Component Analysis Angiogenesis Inhibitors Treatment Outcome Cluster Analysis Retrospective Studies Female Aged Radiomics Male Middle Aged Humans Diabetic Retinopathy
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TriLex: A fusion approach for unsupervised sentiment analysis of short texts.

PloS one Apr 17, 2025
In recent years, online customer reviews and social media platforms have significantly impacted individuals' daily lives. Despite the generally short nature of textual content on these platforms, they convey a wide range of user sentiments. However, ...
Social Media Unsupervised Machine Learning Humans Algorithms
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Unsupervised alignment in neuroscience: Introducing a toolbox for Gromov-Wasserstein optimal transport.

Journal of neuroscience methods Apr 14, 2025
BACKGROUND: Understanding how sensory stimuli are represented across different brains, species, and artificial neural networks is a critical topic in neuroscience. Traditional methods for comparing these representations typically rely on supervised a...
Animals Unsupervised Machine Learning Neurosciences Humans Neural Networks, Computer Brain
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Semantic-consistent diffusion model for unsupervised traumatic brain injury detection and segmentation from computed tomography images.

Medical physics Apr 9, 2025
BACKGROUND: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment abnormal regions, such as cerebral edema and hemorrhages, using only healthy training data. Recent advancements in generative models have achieved suc...
Unsupervised Machine Learning Diffusion Semantics Tomography, X-Ray Computed Image Processing, Computer-Assisted Brain Injuries, Traumatic Humans
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Unsupervised brain MRI tumour segmentation via two-stage image synthesis.

Medical image analysis Apr 5, 2025
Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real...
Image Interpretation, Computer-Assisted Deep Learning Magnetic Resonance Imaging Unsupervised Machine Learning Humans Algorithms Brain Neoplasms
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