|
10861 |
Predicting 30-day mortality in hemophagocytic lymphohistiocytosis: clinical features, biochemical parameters, and machine learning insights
Enthalten in Annals of hematology Bd. 104, 1.3.2025, Nr. 4, date:4.2025: 2239-2264
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10862 |
Predicting 30-day readmission following total knee arthroplasty using machine learning and clinical expertise applied to clinical administrative and research registry data in an Australian cohort
Enthalten in Arthroplasty Bd. 5, 1.6.2023, Nr. 1, date:12.2023: 1-15
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10863 |
Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost
Enthalten in Journal of translational medicine Bd. 18, 7.12.2020, Nr. 1, date:12.2020: 1-14
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10864 |
Predicting 90-day risk of urinary tract infections following urostomy in bladder cancer patients using machine learning and explainability
Enthalten in Scientific reports Bd. 15, 25.2.2025, Nr. 1, date:12.2025: 1-16
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10865 |
Predicting a small molecule-kinase interaction map: A machine learning approach
Enthalten in Journal of cheminformatics Bd. 3, 27.6.2011, Nr. 1, date:12.2011: 1-17
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10866 |
Predicting abatacept retention using machine learning
Enthalten in Arthritis Research & Therapy Bd. 27, 1.2.2025, Nr. 1, date:12.2025: 1-11
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10867 |
Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach
Enthalten in Financial innovation Bd. 9, 3.1.2023, Nr. 1, date:12.2023: 1-23
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10868 |
Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making
Enthalten in Scientific reports Bd. 13, 21.8.2023, Nr. 1, date:12.2023: 1-16
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|
10869 |
Predicting acute kidney injury following open partial nephrectomy treatment using SAT-pruned explainable machine learning model
Enthalten in BMC medical informatics and decision making Bd. 22, 16.5.2022, Nr. 1, date:12.2022: 1-7
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10870 |
Predicting adult neuroscience intensive care unit admission from emergency department triage using a retrospective, tabular-free text machine learning approach
Enthalten in Scientific reports Bd. 11, 14.1.2021, Nr. 1, date:12.2021: 1-9
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Administration
