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26731 |
Retraction Note: Soft electronic material based sensor with optical network in sports application for player movement analysis using machine learning model
Enthalten in Optical and quantum electronics Bd. 56, 13.11.2024, Nr. 11, date:11.2024: 1
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26732 |
Retraction Note: Transmission analysis by using federated machine learning model in optical access networks based multi-agent communication and routing system
Enthalten in Optical and quantum electronics Bd. 56, 19.11.2024, Nr. 12, date:12.2024: 1
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26733 |
Retraining and evaluation of machine learning and deep learning models for seizure classification from EEG data
Enthalten in Scientific reports Bd. 15, 2.5.2025, Nr. 1, date:12.2025: 1-12
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26734 |
Retrieval of nicotine content in cigar leaves by remote analysis of aerial hyperspectral combining machine learning methods
Enthalten in Scientific reports Bd. 15, 31.1.2025, Nr. 1, date:12.2025: 1-14
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26735 |
Retroactive data structure for protein–protein interaction in lung cancer using Dijkstra algorithm
Enthalten in International journal of information technology Bd. 16, 22.12.2023, Nr. 2, date:2.2024: 1239-1251
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26736 |
Retrospective analysis of interpretable machine learning in predicting ICU thrombocytopenia in geriatric ICU patients
Enthalten in Scientific reports Bd. 14, 20.7.2024, Nr. 1, date:12.2024: 1-13
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26737 |
Retrospective Analysis of Radiofrequency Ablation in Patients with Small Solitary Hepatocellular Carcinoma: Survival Outcomes and Development of a Machine Learning Prognostic Model
Enthalten in Current medical science Bd. 44, 30.9.2024, Nr. 5, date:10.2024: 1006-1017
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26738 |
Revealing accuracy in climate dynamics: enhancing evapotranspiration estimation using advanced quantile regression and machine learning models
Enthalten in Applied water science Bd. 14, 24.6.2024, Nr. 7, date:7.2024: 1-22
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26739 |
Revealing Alzheimer’s disease genes spectrum in the whole-genome by machine learning
Enthalten in BMC neurology Bd. 18, 10.1.2018, Nr. 1, date:12.2018: 1-8
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26740 |
Revealing effective regional decarbonisation measures to limit global temperature increase in uncertain transition scenarios with machine learning techniques
Enthalten in Climatic change Bd. 176, 16.6.2023, Nr. 7, date:7.2023: 1-23
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Administration
