AIMC Topic: Unsupervised Machine Learning

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An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images.

Sensors (Basel, Switzerland) Aug 20, 2024
Stroke is the second leading cause of death and a major cause of disability around the world, and the development of atherosclerotic plaques in the carotid arteries is generally considered the leading cause of severe cerebrovascular events. In recent...
Plaque, Atherosclerotic Humans Unsupervised Machine Learning Algorithms Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Carotid Arteries
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Unsupervised machine learning to identify subphenotypes among cardiac intensive care unit patients with heart failure.

ESC heart failure Aug 19, 2024
AIMS: Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac i...
Middle Aged Hospital Mortality Retrospective Studies Humans Unsupervised Machine Learning Follow-Up Studies Intensive Care Units Phenotype Aged Female Survival Rate Male Heart Failure Coronary Care Units
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Definition and Validation of Prognostic Phenotypes in Moderate Aortic Stenosis.

JACC. Cardiovascular imaging Aug 14, 2024
BACKGROUND: Adverse outcomes from moderate aortic stenosis (AS) may be caused by progression to severe AS or by the effects of comorbidities. In the absence of randomized trial evidence favoring aortic valve replacement (AVR) in patients with moderat...
Middle Aged Risk Assessment Comorbidity Humans Predictive Value of Tests Severity of Illness Index Phenotype Heart Failure Time Factors Prognosis Aortic Valve Stenosis Cluster Analysis Aged, 80 and over Female Reproducibility of Results Aortic Valve Male Risk Factors Unsupervised Machine Learning Echocardiography Aged
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Unsupervised machine learning highlights the challenges of subtyping disorders of gut-brain interaction.

Neurogastroenterology and motility Aug 9, 2024
BACKGROUND: Unsupervised machine learning describes a collection of powerful techniques that seek to identify hidden patterns in unlabeled data. These techniques can be broadly categorized into dimension reduction, which transforms and combines the o...
Gastrointestinal Diseases Brain-Gut Axis Humans Unsupervised Machine Learning
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Linear diffusion noise boosted deep image prior for unsupervised sparse-view CT reconstruction.

Physics in medicine and biology Aug 9, 2024
Deep learning has markedly enhanced the performance of sparse-view computed tomography reconstruction. However, the dependence of these methods on supervised training using high-quality paired datasets, and the necessity for retraining under varied p...
Signal-To-Noise Ratio Image Processing, Computer-Assisted Unsupervised Machine Learning Diffusion Tomography, X-Ray Computed Humans Deep Learning
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Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity.

Environmental health perspectives Aug 6, 2024
BACKGROUND: The field of toxicology has witnessed substantial advancements in recent years, particularly with the adoption of new approach methodologies (NAMs) to understand and predict chemical toxicity. Class-based methods such as clustering and cl...
Toxicology Machine Learning Algorithms Cluster Analysis Unsupervised Machine Learning
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ST-Phys: Unsupervised Spatio-Temporal Contrastive Remote Physiological Measurement.

IEEE journal of biomedical and health informatics Aug 6, 2024
Remote photoplethysmography (rPPG) is a non-contact method that employs facial videos for measuring physiological parameters. Existing rPPG methods have achieved remarkable performance. However, the success mainly profits from supervised learning ove...
Video Recording Face Databases, Factual Image Processing, Computer-Assisted Photoplethysmography Unsupervised Machine Learning Remote Sensing Technology Signal Processing, Computer-Assisted Humans Algorithms
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A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.

IEEE journal of biomedical and health informatics Aug 6, 2024
Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic or hypomanic episodes, and depressive episodes. While motor abnormalities are commonly seen during depressive or manic episodes, not much attention has...
Female Young Adult Adult Humans Bipolar Disorder Posture Unsupervised Machine Learning Signal Processing, Computer-Assisted Male Middle Aged Wearable Electronic Devices
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Identifying Factors Associated With Fast Visual Field Progression in Patients With Ocular Hypertension Based on Unsupervised Machine Learning.

Journal of glaucoma Aug 5, 2024
PRCIS: We developed unsupervised machine learning models to identify different subtypes of patients with ocular hypertension in terms of visual field (VF) progression and discovered 4 subtypes with different trends of VF worsening. We then identified...
Risk Factors Aged Cross-Sectional Studies Humans Female Disease Progression Follow-Up Studies Unsupervised Machine Learning Vision Disorders Intraocular Pressure Male Middle Aged Ocular Hypertension Visual Fields Visual Field Tests Glaucoma, Open-Angle
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Towards a rigorous analysis of mutual information in contrastive learning.

Neural networks : the official journal of the International Neural Network Society Aug 2, 2024
Contrastive learning has emerged as a cornerstone in unsupervised representation learning. Its primary paradigm involves an instance discrimination task utilizing InfoNCE loss where the loss has been proven to be a form of mutual information. Consequ...
Neural Networks, Computer Algorithms Learning Unsupervised Machine Learning Humans
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