AIMC Topic: Unsupervised Machine Learning

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Unsupervised Machine Learning-Based Image Recognition of Raw Infrared Spectra: Toward Chemist-like Chemical Structural Classification and Beyond Numerical Data.

Journal of chemical information and modeling Mar 19, 2025
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemic...
Unsupervised Machine Learning Principal Component Analysis Spectrophotometry, Infrared Organic Chemicals Cluster Analysis Machine Learning Image Processing, Computer-Assisted
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Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding.

Journal of chemical theory and computation Mar 19, 2025
A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefor...
Deep Learning Unsupervised Machine Learning Molecular Dynamics Simulation Markov Chains Protein Folding
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CGNet: A Correlation-Guided Registration Network for Unsupervised Deformable Image Registration.

IEEE transactions on medical imaging Mar 17, 2025
Deformable medical image registration plays a significant role in medical image analysis. With the advancement of deep neural networks, learning-based deformable registration methods have made great strides due to their ability to perform fast end-to...
Unsupervised Machine Learning Humans Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Databases, Factual Brain
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Unsupervised learning to identify symptom clusters in older adults undergoing chemotherapy.

Journal of geriatric oncology Mar 14, 2025
INTRODUCTION: Unsupervised machine learning (ML) approaches such as clustering have not been commonly applied to patient-reported data. This study describes ML methods to explore and describe patient-reported symptom trajectories in older adults rece...
Patient Reported Outcome Measures Aged, 80 and over Male Neoplasms Antineoplastic Agents Cluster Analysis Unsupervised Machine Learning Prospective Studies Humans Female Algorithms Aged
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Sustainable visions: unsupervised machine learning insights on global development goals.

PloS one Mar 12, 2025
The 2030 Agenda for Sustainable Development of the United Nations outlines 17 goals for countries of the world to address global challenges in their development. However, the progress of countries towards these goal has been slower than expected and,...
Sustainable Development United Nations Socioeconomic Factors Unsupervised Machine Learning Goals Humans Machine Learning
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Precision soil sampling strategy for the delineation of management zones in olive cultivation using unsupervised machine learning methods.

Scientific reports Mar 10, 2025
Climate change and environmental degradation pose a significant threat to the global community. Soil management is one of the critical factors for achieving climate neutrality, as plants and soils together currently absorb approximately 30% of the CO...
Principal Component Analysis Olea Climate Change Greece Agriculture Cluster Analysis Unsupervised Machine Learning Soil
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Deep Radon Prior: A fully unsupervised framework for sparse-view CT reconstruction.

Computers in biology and medicine Mar 9, 2025
BACKGROUND: Sparse-view computed tomography (CT) substantially reduces radiation exposure but often introduces severe artifacts that compromise image fidelity. Recent advances in deep learning for solving inverse problems have shown considerable prom...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Unsupervised Machine Learning Humans
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Unsupervised Neural Decoding to Predict Dexterous Multi-Finger Flexion and Extension Forces.

IEEE journal of biomedical and health informatics Mar 6, 2025
Accurate control over individual fingers of robotic hands is essential for the progression of human-robot interactions. Accurate prediction of finger forces becomes imperative in this context. The state-of-the-art neural decoders can extract neural s...
Young Adult Adult Male Humans Female Motor Neurons Signal Processing, Computer-Assisted Electromyography Fingers Muscle, Skeletal Unsupervised Machine Learning
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Online Unsupervised Adaptation of Latent Representation for Myoelectric Control During User-Decoder Co-Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 6, 2025
Myoelectric control interfaces, which map electromyographic (EMG) signals into control commands for external devices, have applications in active prosthesis control. However, the statistical characteristics of EMG signals change over time (e.g., beca...
Male User-Computer Interface Muscle, Skeletal Reproducibility of Results Adult Online Systems Humans Unsupervised Machine Learning Algorithms Electromyography Female Artificial Limbs
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Tracking the spatiotemporal evolution of groundwater chemistry in the Quaternary aquifer system of Debrecen area, Hungary: integration of classical and unsupervised learning methods.

Environmental science and pollution research international Mar 1, 2025
Monitoring changes in groundwater quality over time helps identify time-dependent factors influencing water safety and supports the development of effective management strategies. This study investigates the spatiotemporal evolution of groundwater ch...
Groundwater Environmental Monitoring Principal Component Analysis Water Pollutants, Chemical Hungary Cluster Analysis Water Quality Unsupervised Machine Learning
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