AIMC Topic: Unsupervised Machine Learning

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PrediRep: Modeling hierarchical predictive coding with an unsupervised deep learning network.

Neural networks : the official journal of the International Neural Network Society Feb 8, 2025
Hierarchical predictive coding (hPC) provides a compelling framework for understanding how the cortex predicts future sensory inputs by minimizing prediction errors through an internal generative model of the external world. Existing deep learning mo...
Neural Networks, Computer Deep Learning Unsupervised Machine Learning Humans Models, Neurological
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Unsupervised machine learning clustering approach for hospitalized COVID-19 pneumonia patients.

BMC pulmonary medicine Feb 8, 2025
BACKGROUND: Identification of distinct clinical phenotypes of diseases can guide personalized treatment. This study aimed to classify hospitalized COVID-19 pneumonia subgroups using an unsupervised machine learning approach.
Humans Male SARS-CoV-2 Unsupervised Machine Learning COVID-19 Middle Aged Cluster Analysis Hospitalization Proportional Hazards Models Female Aged
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An investigation of microbial groundwater contamination seasonality and extreme weather event interruptions using "big data", time-series analyses, and unsupervised machine learning.

Environmental pollution (Barking, Essex : 1987) Feb 6, 2025
Temporal studies of groundwater potability have historically focused on E. coli detection rates, with non-E. coli coliforms (NEC) and microbial concentrations remaining understudied by comparison. Additionally, "big data" (i.e., large, diverse datase...
Unsupervised Machine Learning Seasons Extreme Weather Water Microbiology Environmental Monitoring Escherichia coli Big Data Groundwater
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CapMatch: Semi-Supervised Contrastive Transformer Capsule With Feature-Based Knowledge Distillation for Human Activity Recognition.

IEEE transactions on neural networks and learning systems Feb 6, 2025
This article proposes a semi-supervised contrastive capsule transformer method with feature-based knowledge distillation (KD) that simplifies the existing semisupervised learning (SSL) techniques for wearable human activity recognition (HAR), called ...
Humans Neural Networks, Computer Algorithms Supervised Machine Learning Pattern Recognition, Automated Human Activities Wearable Electronic Devices Unsupervised Machine Learning
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UTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration.

IEEE transactions on medical imaging Feb 4, 2025
Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based methods. Although ConvNets can eff...
Humans Algorithms Brain Magnetic Resonance Imaging Unsupervised Machine Learning Deep Learning Image Processing, Computer-Assisted
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Facing Differences of Similarity: Intra- and Inter-Correlation Unsupervised Learning for Chest X-Ray Anomaly Detection.

IEEE transactions on medical imaging Feb 4, 2025
Anomaly detection can significantly aid doctors in interpreting chest X-rays. The commonly used strategy involves utilizing the pre-trained network to extract features from normal data to establish feature representations. However, when a pre-trained...
Humans Radiographic Image Interpretation, Computer-Assisted Algorithms Radiography, Thoracic Lung Databases, Factual Unsupervised Machine Learning
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Harmonizing flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization.

Medical image analysis Feb 2, 2025
Lack of standardization and various intrinsic parameters for magnetic resonance (MR) image acquisition results in heterogeneous images across different sites and devices, which adversely affects the generalization of deep neural networks. To alleviat...
Infant, Newborn Adult Image Processing, Computer-Assisted Neural Networks, Computer Brain Magnetic Resonance Imaging Unsupervised Machine Learning Humans
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Identifying Novel Emotions and Wellbeing of Horses from Videos Through Unsupervised Learning.

Sensors (Basel, Switzerland) Jan 31, 2025
This research applies unsupervised learning on a large original dataset of horses in the wild to identify previously unidentified horse emotions. We construct a novel, high-quality, diverse dataset of 3929 images consisting of five wild horse breeds ...
Horses Unsupervised Machine Learning Animals Video Recording Emotions
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Unsupervised, piecewise linear decoding enables an accurate prediction of muscle activity in a multi-task brain computer interface.

Journal of neural engineering Jan 29, 2025
Creating an intracortical brain computer interface (iBCI) capable of seamless transitions between tasks and contexts would greatly enhance user experience. However, the nonlinearity in neural activity presents challenges to computing a global iBCI de...
Macaca mulatta Brain-Computer Interfaces Motor Cortex Algorithms Muscle, Skeletal Unsupervised Machine Learning Animals Electromyography Male
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Discovering patient groups in sequential electronic healthcare data using unsupervised representation learning.

BMC medical informatics and decision making Jan 28, 2025
INTRODUCTION: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Natural Language Processing Humans Electronic Health Records Cluster Analysis Algorithms Child Unsupervised Machine Learning
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