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"Machine Learning"
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29241 - 29250 von 29262
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29241
Wrist accelerometry and machine learning sensitively capture disease progression in prodromal Parkinson’s disease
Enthalten in npj Parkinson's Disease Bd. 11, 17.6.2025, Nr. 1, date:12.2025: 1-7
29242
WSETO: wild stock exchange trading optimization algorithm enabled routing for NB-IoT tracking system
Enthalten in International journal of information technology Bd. 16, 3.9.2024, Nr. 8, date:12.2024: 4895-4905
29243
X-Detect: explainable adversarial patch detection for object detectors in retail
Enthalten in Machine learning Bd. 113, 19.6.2024, Nr. 9, date:9.2024: 6273-6292
29244
X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head
Enthalten in Scientific reports Bd. 15, 20.4.2025, Nr. 1, date:12.2025: 1-13
29245
X-ray Coronary Angiogram images and SYNTAX score to develop Machine-Learning algorithms for CHD Diagnosis
Enthalten in Scientific data Bd. 12, 21.3.2025, Nr. 1, date:12.2025: 1-8
29246
XAI-based cross-ensemble feature ranking methodology for machine learning models
Enthalten in International journal of information technology Bd. 15, 29.4.2023, Nr. 4, date:4.2023: 1759-1768
29247
XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance
Enthalten in Machine learning Bd. 113, 16.7.2024, Nr. 9, date:9.2024: 6871-6910
29248
XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features
Enthalten in International journal of speech technology Bd. 27, 16.10.2024, Nr. 4, date:12.2024: 1055-1083
29249
XGBoost-based machine learning test improves the accuracy of hemorrhage prediction among geriatric patients with long-term administration of rivaroxaban
Enthalten in BMC geriatrics Bd. 23, 10.7.2023, Nr. 1, date:12.2023: 1-12
29250
XGBoost model for predicting erectile dysfunction risk after radical prostatectomy: development and validation using machine learning
Enthalten in Discover oncology Bd. 16, 19.5.2025, Nr. 1, date:12.2025: 1-16
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