|
34631 |
Risk assessment of imported malaria in China: a machine learning perspective
Enthalten in BMC public health Bd. 24, 20.3.2024, Nr. 1, date:12.2024: 1-12
|
|
|
|
34632 |
Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study
Enthalten in Scientific reports Bd. 15, 30.1.2025, Nr. 1, date:12.2025: 1-10
|
|
|
|
34633 |
Risk factor mining and prediction of urine protein progression in chronic kidney disease: a machine learning- based study
Enthalten in BMC medical informatics and decision making Bd. 23, 31.8.2023, Nr. 1, date:12.2023: 1-17
|
|
|
|
34634 |
Risk factors affecting patients survival with colorectal cancer in Morocco: survival analysis using an interpretable machine learning approach
Enthalten in Scientific reports Bd. 14, 12.2.2024, Nr. 1, date:12.2024: 1-13
|
|
|
|
34635 |
Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
Enthalten in Scientific reports Bd. 13, 20.2.2023, Nr. 1, date:12.2023: 1-11
|
|
|
|
34636 |
Risk factors and machine learning prediction models for intrahepatic cholestasis of pregnancy
Enthalten in BMC pregnancy and childbirth Bd. 25, 30.1.2025, Nr. 1, date:12.2025: 1-20
|
|
|
|
34637 |
Risk factors and predictive models for post-operative moderate-to-severe mitral regurgitation following transcatheter aortic valve replacement: a machine learning approach
Enthalten in BMC cardiovascular disorders Bd. 25, 10.5.2025, Nr. 1, date:12.2025: 1-12
|
|
|
|
34638 |
Risk factors and socio-economic burden in pancreatic ductal adenocarcinoma operation: a machine learning based analysis
Enthalten in BMC cancer Bd. 20, 27.11.2020, Nr. 1, date:12.2020: 1-12
|
|
|
|
34639 |
Risk Factors Associated with COVID-19 Lethality: A Machine Learning Approach Using Mexico Database
Enthalten in Journal of medical systems Bd. 47, 19.8.2023, Nr. 1, date:12.2023: 1-11
|
|
|
|
34640 |
Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse
Enthalten in Intensive Care Medicine Experimental Bd. 9, 28.6.2021, Nr. 1, date:12.2021: 1-15
|
|
Administration
