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tit all "Machine Learning Techniques"
im Bestand: Gesamter Bestand
511 - 520 von 542
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511
Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques
Enthalten in BMC medical research methodology Bd. 20, 16.11.2020, Nr. 1, date:12.2020: 1-14
512
Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques
Enthalten in Scientific reports Bd. 14, 29.1.2024, Nr. 1, date:12.2024: 1-12
513
Symptom clusters among cancer survivors: what can machine learning techniques tell us?
Enthalten in BMC medical research methodology Bd. 21, 16.8.2021, Nr. 1, date:12.2021: 1-12
514
Synergistic integration of Multi-View Brain Networks and advanced machine learning techniques for auditory disorders diagnostics
Enthalten in Brain Informatics Bd. 11, 14.1.2024, Nr. 1, date:12.2024: 1-13
515
Synergizing quantum techniques with machine learning for advancing drug discovery challenge
Enthalten in Scientific reports Bd. 14, 28.12.2024, Nr. 1, date:12.2024: 1-12
516
Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques
Enthalten in Scientific reports Bd. 13, 22.9.2023, Nr. 1, date:12.2023: 1-15
517
The application of machine learning techniques in posttraumatic stress disorder: a systematic review and meta-analysis
Enthalten in npj digital medicine Bd. 7, 9.5.2024, Nr. 1, date:12.2024: 1-13
518
The atmospheric boundary layer: a review of current challenges and a new generation of machine learning techniques
Enthalten in Artificial intelligence review Bd. 57, 17.10.2024, Nr. 12, date:12.2024: 1-51
519
The effect of resampling techniques on the performances of machine learning clinical risk prediction models in the setting of severe class imbalance: development and internal validation in a retrospective cohort
Enthalten in Discover artificial intelligence Bd. 4, 26.11.2024, Nr. 1, date:12.2024: 1-17
520
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Enthalten in Stochastic environmental research and risk assessment Bd. 38, 13.6.2024, Nr. 8, date:8.2024: 3273-3290
511 - 520 von 542
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