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11191 |
Predictors for extubation failure in COVID-19 patients using a machine learning approach Enthalten in Critical care Bd. 25, 27.12.2021, Nr. 1, date:12.2021: 1-10
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11192 |
Predictors of Adherence to Stroke Prevention in the BALKAN-AF Study: A Machine-Learning Approach Enthalten in TH open Bd. 06, 2022, Nr. 03: e283-e290
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11193 |
Predictors of depression among Chinese college students: a machine learning approach Enthalten in BMC public health Bd. 25, 5.2.2025, Nr. 1, date:12.2025: 1-11
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11194 |
Predictors of High Healthcare Cost Among Patients with Generalized Myasthenia Gravis: A Combined Machine Learning and Regression Approach from a US Payer Perspective Enthalten in Applied health economics and health policy Bd. 22, 13.7.2024, Nr. 5, date:9.2024: 735-747
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11195 |
Predictors of remission from body dysmorphic disorder after internet-delivered cognitive behavior therapy: a machine learning approach Enthalten in BMC psychiatry Bd. 20, 19.5.2020, Nr. 1, date:12.2020: 1-9
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11196 |
Predictors of shorter- and longer-term mortality after COVID-19 presentation among dialysis patients: parallel use of machine learning models in Latin and North American countries Enthalten in BMC nephrology Bd. 23, 22.10.2022, Nr. 1, date:12.2022: 1-23
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11197 |
PREFACE – HYPERSPECTRAL SENSING MEETS MACHINE LEARNING AND PATTERN ANALYSIS (HYPERMLPA 2019) Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. IV-2/W5, 2019: 607-608
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11198 |
PREFACE – ISPRS WORKSHOP HYPERSPECTRAL SENSING MEETS MACHINE LEARNING AND PATTERN ANALYSIS (HYPERMLPA 2019) Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-2/W13, 2019: 1825-1826
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11199 |
Preference of musculoskeletal pain treatment in middle-aged and elderly chinese people: a machine learning analysis of the China health and retirement longitudinal study Enthalten in BMC musculoskeletal disorders Bd. 24, 29.6.2023, Nr. 1, date:12.2023: 1-13
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11200 |
Prehospital diagnostic algorithm for acute coronary syndrome using machine learning: a prospective observational study Enthalten in Scientific reports Bd. 12, 26.8.2022, Nr. 1, date:12.2022: 1-9
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