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Ergebnis der Suche nach: "Machine Learning"
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16241 - 16250 von 16533
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Artikel 16241 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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Artikel 16242 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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Artikel 16243 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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Artikel 16244 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
Online Ressource
Artikel 16245 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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Artikel 16246 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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Artikel 16247 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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Artikel 16248 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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Artikel 16249 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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Artikel 16250 Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models
Enthalten in BMC medicine Bd. 23, 19.5.2025, Nr. 1, date:12.2025: 1-12
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