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25921 |
Prophylactic and therapeutic measures for emerging and re-emerging viruses: artificial intelligence and machine learning - the key to a promising future
Enthalten in Health and Technology Bd. 14, 24.1.2024, Nr. 2, date:3.2024: 251-261
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25922 |
Proportion-based normalizations outperform compositional data transformations in machine learning applications
Enthalten in Microbiome Bd. 12, 5.3.2024, Nr. 1, date:12.2024: 1-13
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25923 |
Proportional impact prediction model of coating material on nitrate leaching of slow-release Urea Super Granules (USG) using machine learning and RSM technique
Enthalten in Scientific reports Bd. 14, 6.2.2024, Nr. 1, date:12.2024: 1-18
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25924 |
Proposal and evaluation of tsunami disaster drill support system using tablet computer
Enthalten in International journal of information technology Bd. 15, 13.9.2023, Nr. 8, date:12.2023: 4029-4039
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25925 |
Proposal of a new equation for estimating resting energy expenditure of acute kidney injury patients on dialysis: a machine learning approach
Enthalten in Nutrition & metabolism Bd. 17, 17.11.2020, Nr. 1, date:12.2020: 1-8
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25926 |
Proposed numerical and machine learning models for fiber-reinforced polymer concrete-steel hollow and solid elliptical columns
Enthalten in Frontiers of structural and civil engineering Bd. 18, 26.7.2024, Nr. 8, date:8.2024: 1169-1194
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25927 |
Proposing a digital twin-based sustainable water governance system for rural Indian villages
Enthalten in International journal of information technology Bd. 17, 18.1.2025, Nr. 3, date:4.2025: 1777-1783
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25928 |
Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study
Enthalten in BMC pregnancy and childbirth Bd. 21, 12.3.2021, Nr. 1, date:12.2021: 1-17
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25929 |
Proposing a machine learning-based model for predicting nonreassuring fetal heart
Enthalten in Scientific reports Bd. 15, 6.3.2025, Nr. 1, date:12.2025: 1-8
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25930 |
Proposing a short version of the Unesp-Botucatu pig acute pain scale using a novel application of machine learning technique
Enthalten in Scientific reports Bd. 15, 28.2.2025, Nr. 1, date:12.2025: 1-11
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