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25831 |
Prediction of prognosis of immune checkpoint inhibitors combined with anti-angiogenic agents for unresectable hepatocellular carcinoma by machine learning-based radiomics
Enthalten in BMC cancer Bd. 25, 19.5.2025, Nr. 1, date:12.2025: 1-18
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25832 |
Prediction of prognosis, efficacy of lung adenocarcinoma by machine learning model based on immune and metabolic related genes
Enthalten in Discover oncology Bd. 15, 18.12.2024, Nr. 1, date:12.2024: 1-16
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25833 |
Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective
Enthalten in Scientific reports Bd. 14, 4.12.2024, Nr. 1, date:12.2024: 1-12
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25834 |
Prediction of properties of friction stir spot welded joints of AA7075-T651/Ti-6Al-4V alloy using machine learning algorithms
Enthalten in Archives of civil and mechanical engineering Bd. 22, 21.3.2022, Nr. 2, date:5.2022: 1-19
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25835 |
Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study
Enthalten in Egyptian National Cancer Institute (al-Qāhira): Journal of the Egyptian National Cancer Institute Bd. 37, 17.3.2025, Nr. 1, date:12.2025: 1-8
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25836 |
Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning
Enthalten in Nature biotechnology Bd. 40, 23.5.2022, Nr. 10, date:10.2022: 1520-1527
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25837 |
Prediction of Protein–Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures
Enthalten in The journal of membrane biology Bd. 249, 12.11.2015, Nr. 1-2, date:4.2016: 141-153
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25838 |
Prediction of Pseudoprogression versus Progression using Machine Learning Algorithm in Glioblastoma
Enthalten in Scientific reports Bd. 8, 21.8.2018, Nr. 1, date:12.2018: 1-9
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25839 |
Prediction of Pt, Ir, Ru, and Rh complexes light absorption in the therapeutic window for phototherapy using machine learning
Enthalten in Journal of cheminformatics Bd. 17, 5.1.2025, Nr. 1, date:12.2025: 1-13
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25840 |
Prediction of pulmonary embolism by an explainable machine learning approach in the real world
Enthalten in Scientific reports Bd. 15, 4.1.2025, Nr. 1, date:12.2025: 1-8
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Administration
