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11641 - 11650 von 15142

	11641	Machine learning models for identifying predictors of clinical outcomes with first-line immune checkpoint inhibitor therapy in advanced non-small cell lung cancer Enthalten in Scientific reports Bd. 12, 21.10.2022, Nr. 1, date:12.2022: 1-13
	11642	Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients Enthalten in Scientific reports Bd. 15, 13.4.2025, Nr. 1, date:12.2025: 1-15
	11643	Machine learning models for online detection of wear and friction behaviour of biomedical graded stainless steel 316L under lubricating conditions Enthalten in The international journal of advanced manufacturing technology Bd. 128, 9.8.2023, Nr. 5-6, date:9.2023: 2671-2688
	11644	Machine learning models for optimization, validation, and prediction of light emitting diodes with kinetin based basal medium for in vitro regeneration of upland cotton (Gossypium hirsutum L.) Enthalten in Journal of cotton research Bd. 8, 14.5.2025, Nr. 1, date:12.2025: 1-14
	11645	Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles Enthalten in Scientific reports Bd. 15, 31.3.2025, Nr. 1, date:12.2025: 1-11
	11646	Machine learning models for performance estimation of solar still in a humid sub-tropical region Enthalten in Discover atmosphere Bd. 3, 15.7.2025, Nr. 1, date:12.2025: 1-17
	11647	Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores Enthalten in Scientific reports Bd. 14, 30.5.2024, Nr. 1, date:12.2024: 1-17
	11648	Machine learning models for predicting early hemorrhage progression in traumatic brain injury Enthalten in Scientific reports Bd. 14, 22.5.2024, Nr. 1, date:12.2024: 1-10
	11649	Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials Enthalten in Scientific reports Bd. 15, 28.1.2025, Nr. 1, date:12.2025: 1-19
	11650	Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics Enthalten in Journal of translational medicine Bd. 23, 28.3.2025, Nr. 1, date:12.2025: 1-14

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