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26941 |
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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26942 |
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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26943 |
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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26944 |
Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain
Enthalten in Scientific reports Bd. 14, 12.8.2024, Nr. 1, date:12.2024: 1-24
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26945 |
Utilizing machine learning to classify persistent organic pollutants in the serum of pregnant women: a predictive modeling approach
Enthalten in Environmental science and pollution research Bd. 31, 21.8.2024, Nr. 40, date:8.2024: 52980-52995
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26946 |
Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke
Enthalten in BMC neurology Bd. 24, 7.5.2024, Nr. 1, date:12.2024: 1-12
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26947 |
Utilizing machine learning to identify fall predictors in India's aging population: findings from the LASI
Enthalten in BMC geriatrics Bd. 25, 17.3.2025, Nr. 1, date:12.2025: 1-11
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26948 |
Utilizing machine learning to model interdependency of bulk molecular weight, solution concentration, and thickness of spin coated polystyrene thin films
Enthalten in Materials Research Society: MRS communications Bd. 14, 12.2.2024, Nr. 2, date:4.2024: 230-236
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26949 |
Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine)
Enthalten in Scientific reports Bd. 15, 24.1.2025, Nr. 1, date:12.2025: 1-13
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26950 |
Utilizing machine learning to predict participant response to follow-up health surveys in the Millennium Cohort Study
Enthalten in Scientific reports Bd. 14, 28.10.2024, Nr. 1, date:12.2024: 1-12
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Administration
