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11011 |
Predicting total healthcare demand using machine learning: separate and combined analysis of predisposing, enabling, and need factors
Enthalten in BMC health services research Bd. 25, 12.3.2025, Nr. 1, date:12.2025: 1-27
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11012 |
PREDICTING TRAFFIC CONGESTION DURING COVID19 USING HUMAN MOBILITY AND STREET-WASTE FEATURES
Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-4/W3-2022, 2022: 301-308. 8 S.
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11013 |
Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models
Enthalten in Pain and therapy Bd. 14, 25.12.2024, Nr. 1, date:2.2025: 359-373
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11014 |
Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis
Enthalten in Translational Psychiatry Bd. 12, 12.8.2022, Nr. 1, date:12.2022: 1-18
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11015 |
Predicting triage of pediatric patients in the emergency department using machine learning approach
Enthalten in International journal of emergency medicine Bd. 18, 10.3.2025, Nr. 1, date:12.2025: 1-12
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11016 |
Predicting two-year survival versus non-survival after first myocardial infarction using machine learning and Swedish national register data
Enthalten in BMC medical informatics and decision making Bd. 17, 5.7.2017, Nr. 1, date:12.2017: 1-11
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11017 |
Predicting type 2 diabetes via machine learning integration of multiple omics from human pancreatic islets
Enthalten in Scientific reports Bd. 14, 25.6.2024, Nr. 1, date:12.2024: 1-17
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11018 |
Predicting unplanned medical visits among patients with diabetes: translation from machine learning to clinical implementation
Enthalten in BMC medical informatics and decision making Bd. 21, 31.3.2021, Nr. 1, date:12.2021: 1-11
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11019 |
Predicting unplanned readmission due to cardiovascular disease in hospitalized patients with cancer: a machine learning approach
Enthalten in Scientific reports Bd. 13, 18.8.2023, Nr. 1, date:12.2023: 1-9
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11020 |
Predicting vehicle prices via quantum-assisted feature selection
Enthalten in International journal of information technology Bd. 15, 21.7.2023, Nr. 6, date:8.2023: 2897-2905
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Administration
