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36141 |
Utilizing Machine Learning and DSAS to Analyze Historical Trends and Forecast Future Shoreline Changes Along the River Niger, Niger Delta
Enthalten in Water conservation science and engineering Bd. 9, 10.12.2024, Nr. 2, date:12.2024: 1-21
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36142 |
Utilizing machine learning and molecular dynamics for enhanced drug delivery in nanoparticle systems
Enthalten in Scientific reports Bd. 14, 4.11.2024, Nr. 1, date:12.2024: 1-17
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36143 |
Utilizing machine learning approaches to investigate the relationship between cystatin C and serious complications in esophageal cancer patients after esophagectomy
Enthalten in Supportive care in cancer Bd. 33, 16.12.2024, Nr. 1, date:1.2025: 1-14
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36144 |
Utilizing machine learning approaches within concrete technology offers an intelligent perspective towards sustainability in the construction industry: a comprehensive review
Enthalten in Multiscale and multidisciplinary modeling, experiments and design Bd. 8, 26.10.2024, Nr. 1, date:1.2025: 1-24
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36145 |
Utilizing machine learning-based QSAR model to overcome standalone consensus docking limitation in beta-lactamase inhibitors screening: a proof-of-concept study
Enthalten in BMC chemistry Bd. 18, 20.12.2024, Nr. 1, date:12.2024: 1-16
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36146 |
Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department
Enthalten in BMC medical research methodology Bd. 21, 17.4.2021, Nr. 1, date:12.2021: 1-13
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36147 |
Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification
Enthalten in Scientific reports Bd. 14, 20.2.2024, Nr. 1, date:12.2024: 1-29
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36148 |
Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines
Enthalten in Annals of surgical oncology Bd. 27, 6.11.2019, Nr. 3, date:3.2020: 866-874
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36149 |
Utilizing machine learning models to grasp water quality dynamic changes in lake eutrophication through phytoplankton parameters
Enthalten in Frontiers of environmental science & engineering Bd. 19, 18.11.2024, Nr. 2, date:2.2025: 1-16
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36150 |
Utilizing Machine Learning Models with Limited Meteorological Data as Alternatives for the FAO-56PM Model in Estimating Reference Evapotranspiration
Enthalten in Water resources management Bd. 38, 7.2.2024, Nr. 6, date:4.2024: 1921-1942
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