|
25991 |
Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability compared with the modified early warning score
Enthalten in Critical care Bd. 16, 21.6.2012, Nr. 3, date:6.2012: 1-12
|
|
|
|
25992 |
Prediction of CBR and resilient modulus of crushed waste rocks using machine learning models
Enthalten in Acta geotechnica Bd. 17, 2.4.2022, Nr. 4, date:4.2022: 1383-1402
|
|
|
|
25993 |
Prediction of cell migration potential on human breast cancer cells treated with Albizia lebbeck ethanolic extract using extreme machine learning
Enthalten in Scientific reports Bd. 13, 14.12.2023, Nr. 1, date:12.2023: 1-16
|
|
|
|
25994 |
Prediction of cellulose micro/nanofiber aspect ratio and yield of nanofibrillation using machine learning techniques
Enthalten in Cellulose Bd. 29, 17.9.2022, Nr. 17, date:11.2022: 9143-9162
|
|
|
|
25995 |
Prediction of central deflection and slenderness limit for lateral stability of simply supported concrete beam using machine learning techniques
Enthalten in Asian journal of civil engineering Bd. 25, 26.7.2024, Nr. 7, date:11.2024: 5443-5466
|
|
|
|
25996 |
Prediction of cerebral aneurysm rupture risk by machine learning algorithms: a systematic review and meta-analysis of 18,670 participants
Enthalten in Neurosurgical review Bd. 47, 6.1.2024, Nr. 1, date:12.2024: 1-17
|
|
|
|
25997 |
Prediction of Cervical Cancer from Behavior Risk Using Machine Learning Techniques
Enthalten in SN Computer Science Bd. 2, 30.3.2021, Nr. 3, date:5.2021: 1-10
|
|
|
|
25998 |
Prediction of chemoresistance trait of cancer cell lines using machine learning algorithms and systems biology analysis
Enthalten in Journal of Big Data Bd. 8, 5.7.2021, Nr. 1, date:12.2021: 1-21
|
|
|
|
25999 |
Prediction of childbearing tendency in women on the verge of marriage using machine learning techniques
Enthalten in Scientific reports Bd. 14, 6.9.2024, Nr. 1, date:12.2024: 1-10
|
|
|
|
26000 |
Prediction of chromosomal abnormalities in the screening of the first trimester of pregnancy using machine learning methods: a study protocol
Enthalten in Reproductive health Bd. 21, 3.7.2024, Nr. 1, date:12.2024: 1-5
|
|
Administration
