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26621 |
The efficacy of canagliflozin in diabetes subgroups stratified by data-driven clustering or a supervised machine learning method: a post hoc analysis of canagliflozin clinical trial data
Enthalten in Diabetologia Bd. 65, 8.7.2022, Nr. 9, date:9.2022: 1424-1435
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26622 |
The efficacy of machine learning algorithm for raw drug authentication in Coscinium fenestratum (Gaertn.) Colebr. employing a DNA barcode database
Enthalten in Physiology and molecular biology of plants Bd. 27, 15.3.2021, Nr. 3, date:3.2021: 605-617
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26623 |
The efficacy of machine learning models in forecasting treatment failure in thoracolumbar burst fractures treated with short-segment posterior spinal fixation
Enthalten in Journal of orthopaedic surgery and research Bd. 19, 1.4.2024, Nr. 1, date:12.2024: 1-7
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26624 |
The efficiency of machine learning-assisted platform for article screening in systematic reviews in orthopaedics
Enthalten in International orthopaedics Bd. 47, 23.12.2022, Nr. 2, date:2.2023: 551-556
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26625 |
The ethics of machine learning-based clinical decision support: an analysis through the lens of professionalisation theory
Enthalten in BMC medical ethics Bd. 22, 19.8.2021, Nr. 1, date:12.2021: 1-9
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26626 |
THE EXPLAINABILITY OF GRADIENT-BOOSTED DECISION TREES FOR DIGITAL ELEVATION MODEL (DEM) ERROR PREDICTION
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-M-3-2023, 2023: 161-168. 8 S.
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26627 |
The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population
Enthalten in Skeletal radiology Bd. 49, 23.11.2019, Nr. 4, date:4.2020: 613-618
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26628 |
The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches
Enthalten in Arthritis Research & Therapy Bd. 21, 9.11.2019, Nr. 1, date:12.2019: 1-10
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26629 |
The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model
Enthalten in La Radiologia medica Bd. 129, 21.3.2024, Nr. 5, date:5.2024: 751-766
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26630 |
The Firm Life Cycle Forecasting Model Using Machine Learning Based on News Articles
Enthalten in International journal of networked and distributed computing Bd. 9, 5.1.2021, Nr. 1, date:1.2021: 1-9
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