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25581 |
Predicting positron emission tomography brain amyloid positivity using interpretable machine learning models with wearable sensor data and lifestyle factors
Enthalten in Alzheimer's research & therapy Bd. 15, 12.12.2023, Nr. 1, date:12.2023: 1-19
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25582 |
Predicting post-operative vault and optimal implantable collamer lens size using machine learning based on various ophthalmic device combinations
Enthalten in Biomedical engineering online Bd. 22, 15.6.2023, Nr. 1, date:12.2023: 1-15
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25583 |
Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning
Enthalten in Journal of neuro-oncology Bd. 169, 24.5.2024, Nr. 1, date:8.2024: 175-185
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25584 |
Predicting postoperative delirium after hip arthroplasty for elderly patients using machine learning
Enthalten in Aging clinical and experimental research Bd. 35, 13.4.2023, Nr. 6, date:6.2023: 1241-1251
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25585 |
Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology
Enthalten in BMC medical informatics and decision making Bd. 23, 31.3.2023, Nr. 1, date:12.2023: 1-8
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25586 |
Predicting postoperative nausea and vomiting using machine learning: a model development and validation study
Enthalten in BMC anesthesiology Bd. 25, 20.3.2025, Nr. 1, date:12.2025: 1-11
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25587 |
Predicting postoperative pulmonary infection in elderly patients undergoing major surgery: a study based on logistic regression and machine learning models
Enthalten in BMC pulmonary medicine Bd. 25, 19.3.2025, Nr. 1, date:12.2025: 1-13
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25588 |
Predicting postoperative rehemorrhage in hypertensive intracerebral hemorrhage using noncontrast CT radiomics and clinical data with an interpretable machine learning approach
Enthalten in Scientific reports Bd. 14, 27.4.2024, Nr. 1, date:12.2024: 1-12
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25589 |
Predicting potential reforestation areas by Quercus ilex (L.) species using machine learning algorithms: case of upper Ziz, southeastern Morocco
Enthalten in Environmental monitoring and assessment Bd. 195, 25.8.2023, Nr. 9, date:9.2023: 1-20
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25590 |
Predicting Powder Blend Flowability from Individual Constituent Properties Using Machine Learning
Enthalten in Pharmaceutical research Bd. 42, 17.4.2025, Nr. 4, date:4.2025: 665-683
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