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25521 |
Predicting Clinical Remission of Chronic Urticaria Using Random Survival Forests: Machine Learning Applied to Real-World Data
Enthalten in Dermatology and therapy Bd. 12, 27.10.2022, Nr. 12, date:12.2022: 2747-2763
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25522 |
Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches
Enthalten in Journal of neuroEngineering and rehabilitation Bd. 17, 29.9.2020, Nr. 1, date:12.2020: 1-10
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25523 |
Predicting Code Smells and Analysis of Predictions: Using Machine Learning Techniques and Software Metrics
Enthalten in Journal of computer science and technology Bd. 35, 30.11.2020, Nr. 6, date:11.2020: 1428-1445
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25524 |
Predicting coefficient of permeability of soils: an interpretable machine learning approach augmented by deep generative adversarial network
Enthalten in Multiscale and multidisciplinary modeling, experiments and design Bd. 8, 16.1.2025, Nr. 2, date:2.2025: 1-22
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25525 |
Predicting coffee yield based on agroclimatic data and machine learning
Enthalten in Theoretical and applied climatology Bd. 148, 21.2.2022, Nr. 3-4, date:5.2022: 899-914
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25526 |
Predicting cognitive dysfunction and regional hubs using Braak staging amyloid-beta biomarkers and machine learning
Enthalten in Brain Informatics Bd. 10, 3.12.2023, Nr. 1, date:12.2023: 1-14
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25527 |
Predicting cognitive frailty in community-dwelling older adults: a machine learning approach based on multidomain risk factors
Enthalten in Scientific reports Bd. 15, 26.5.2025, Nr. 1, date:12.2025: 1-12
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25528 |
Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment
Enthalten in BMC medicine Bd. 22, 25.1.2024, Nr. 1, date:12.2024: 1-14
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25529 |
Predicting common solid renal tumors using machine learning models of classification of radiologist-assessed magnetic resonance characteristics
Enthalten in Abdominal radiology Bd. 45, 14.7.2020, Nr. 9, date:9.2020: 2797-2809
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25530 |
Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study
Enthalten in Zeitschrift für Kinderheilkunde Bd. 183, 18.4.2024, Nr. 7, date:7.2024: 2983-2993
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