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10781 |
Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology Enthalten in BMC gastroenterology Bd. 25, 18.4.2025, Nr. 1, date:12.2025: 1-13
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10782 |
Optimizing prognostic factors of five-year survival in gastric cancer patients using feature selection techniques with machine learning algorithms: a comparative study Enthalten in BMC medical informatics and decision making Bd. 23, 6.4.2023, Nr. 1, date:12.2023: 1-16
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10783 |
Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences Enthalten in Insights into imaging Bd. 15, 4.11.2024, Nr. 1, date:12.2024: 1-16
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10784 |
Optimizing smart home energy management for sustainability using machine learning techniques Enthalten in Discover sustainability Bd. 5, 25.11.2024, Nr. 1, date:12.2024: 1-24
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10785 |
Optimizing solar power efficiency in smart grids using hybrid machine learning models for accurate energy generation prediction Enthalten in Scientific reports Bd. 14, 24.7.2024, Nr. 1, date:12.2024: 1-25
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10786 |
Optimizing structural integrity of a pressure vessel via finite element analysis and machine learning based XGBoost approaches Enthalten in Scientific reports Bd. 15, 3.4.2025, Nr. 1, date:12.2025: 1-21
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10787 |
Optimizing Trajectories for Cranial Laser Interstitial Thermal Therapy Using Computer-Assisted Planning: A Machine Learning Approach Enthalten in Neurotherapeutics Bd. 16, 5.12.2018, Nr. 1, date:1.2019: 182-191
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10788 |
Optimizing warfarin dosing for patients with atrial fibrillation using machine learning Enthalten in Scientific reports Bd. 14, 24.2.2024, Nr. 1, date:12.2024: 1-13
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10789 |
Optimum Combination of Spectral Variables for Crop Mapping in Heterogeneous Landscapes based on Sentinel-2 Time Series and Machine Learning Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-3-2024, 2024: 85-92. 8 S.
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10790 |
Optoelectronic performance prediction of HgCdTe homojunction photodetector in long wave infrared spectral region using traditional simulations and machine learning models Enthalten in Scientific reports Bd. 14, 15.11.2024, Nr. 1, date:12.2024: 1-28
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