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16221 |
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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16222 |
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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16223 |
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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16224 |
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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16225 |
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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16226 |
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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16227 |
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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16228 |
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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16229 |
Unveiling Adolescent Suicidality: Holistic Analysis of Protective and Risk Factors Using Multiple Machine Learning Algorithms
Enthalten in Journal of youth and adolescence Bd. 53, 20.11.2023, Nr. 3, date:3.2024: 507-525
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16230 |
Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach
Enthalten in Scientific reports Bd. 15, 26.4.2025, Nr. 1, date:12.2025: 1-18
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