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Ergebnis der Suche nach:
"Machine Learning"
im Bestand: Gesamter Bestand
15611 - 15620 von 17051
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15611
Prognostic effects of glycaemic variability on diastolic heart failure and type 2 diabetes mellitus: insights and 1-year mortality machine learning prediction model
Enthalten in Diabetology & metabolic syndrome Bd. 16, 23.11.2024, Nr. 1, date:12.2024: 1-15
15612
Prognostic model for log odds of negative lymph node in locally advanced rectal cancer via interpretable machine learning
Enthalten in Scientific reports Bd. 15, 7.3.2025, Nr. 1, date:12.2025: 1-13
15613
Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses
Enthalten in Discover oncology Bd. 16, 24.5.2025, Nr. 1, date:12.2025: 1-28
15614
Prognostic models for upper urinary tract urothelial carcinoma patients after radical nephroureterectomy based on a novel systemic immune-inflammation score with machine learning
Enthalten in BMC cancer Bd. 23, 22.6.2023, Nr. 1, date:12.2023: 1-15
15615
Prognostic nutritional index and diabetic peripheral neuropathy in type 2 diabetes: a machine learning approach
Enthalten in Nutrition & metabolism Bd. 22, 25.3.2025, Nr. 1, date:12.2025: 1-10
15616
Prognostic prediction for HER2-low breast cancer patients using a novel machine learning model
Enthalten in BMC cancer Bd. 24, 29.11.2024, Nr. 1, date:12.2024: 1-15
15617
Prognostic risk modeling of endometrial cancer using programmed cell death-related genes: a comprehensive machine learning approach
Enthalten in Discover oncology Bd. 16, 8.3.2025, Nr. 1, date:12.2025: 1-18
15618
Prognostic significance of chest CT severity score in mortality prediction of COVID-19 patients, a machine learning study
Enthalten in The Egyptian Journal of Radiology and Nuclear Medicine Bd. 54, 20.4.2023, Nr. 1, date:12.2023: 1-9
15619
Prognostic significance of migrasomes in neuroblastoma through machine learning and multi-omics
Enthalten in Scientific reports Bd. 14, 18.7.2024, Nr. 1, date:12.2024: 1-16
15620
Prognostic subgroups of chronic pain patients using latent variable mixture modeling within a supervised machine learning framework
Enthalten in Scientific reports Bd. 14, 31.5.2024, Nr. 1, date:12.2024: 1-12
15611 - 15620 von 17051
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