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26831 |
Unsupervised machine learning for disease prediction: a comparative performance analysis using multiple datasets
Enthalten in Health and Technology Bd. 14, 29.12.2023, Nr. 1, date:1.2024: 141-154
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26832 |
Unsupervised machine learning for local stress identification in fatigue analysis of welded joints
Enthalten in Welding in the world Bd. 69, 19.11.2024, Nr. 1, date:1.2025: 213-226
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26833 |
Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data
Enthalten in Acta Neuropathologica Communications Bd. 11, 21.12.2023, Nr. 1, date:12.2023: 1-20
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26834 |
Unsupervised machine learning identifies distinct phenotypes in cardiac complications of pediatric patients treated with anthracyclines
Enthalten in Cardio-Oncology Bd. 10, 28.10.2024, Nr. 1, date:12.2024: 1-11
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26835 |
Unsupervised machine-learning method for improving the performance of ambulatory fall-detection systems
Enthalten in Biomedical engineering online Bd. 11, 16.2.2012, Nr. 1, date:12.2012: 1-11
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26836 |
Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population
Enthalten in Scientific reports Bd. 13, 11.10.2023, Nr. 1, date:12.2023: 1-11
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26837 |
Unsupervised Machine Learning Methods for Determining Special Points of the Polymerase Chain Reaction Fluorescence Accumulation Curve
Enthalten in Moskovskij gosudarstvennyj universitet im. M.V. Lomonosova: Moscow University physics bulletin Bd. 78, 17.1.2024, Nr. 1, date:12.2023: S169-S179
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26838 |
Unsupervised Machine Learning Revealed that Repeat Transcranial Magnetic Stimulation is More Suitable for Stroke Patients with Statin
Enthalten in Neurology and Therapy Bd. 13, 30.4.2024, Nr. 3, date:6.2024: 857-868
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26839 |
Unsupervised machine learning to investigate trajectory patterns of COVID-19 symptoms and physical activity measured via the MyHeart Counts App and smart devices
Enthalten in npj digital medicine Bd. 6, 22.12.2023, Nr. 1, date:12.2023: 1-11
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26840 |
UNSUPERVISED METHODOLOGY TO IN-SEASON MAPPING OF SUMMER CROPS IN URUGUAY WITH MODIS EVI’S TEMPORAL SERIES AND MACHINE LEARNING
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-3/W12-2020, 2020: 171-176
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