|
26271 |
Proposing a digital twin-based sustainable water governance system for rural Indian villages
Enthalten in International journal of information technology Bd. 17, 18.1.2025, Nr. 3, date:4.2025: 1777-1783
|
|
|
|
26272 |
Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study
Enthalten in BMC pregnancy and childbirth Bd. 21, 12.3.2021, Nr. 1, date:12.2021: 1-17
|
|
|
|
26273 |
Proposing a machine learning-based model for predicting nonreassuring fetal heart
Enthalten in Scientific reports Bd. 15, 6.3.2025, Nr. 1, date:12.2025: 1-8
|
|
|
|
26274 |
Proposing a short version of the Unesp-Botucatu pig acute pain scale using a novel application of machine learning technique
Enthalten in Scientific reports Bd. 15, 28.2.2025, Nr. 1, date:12.2025: 1-11
|
|
|
|
26275 |
Proposing an ensemble machine learning based drought vulnerability index using M5P, dagging, random sub-space and rotation forest models
Enthalten in Stochastic environmental research and risk assessment Bd. 37, 6.3.2023, Nr. 7, date:7.2023: 2513-2540
|
|
|
|
26276 |
Prospective prediction of PTSD diagnosis in a nationally representative sample using machine learning
Enthalten in BMC psychiatry Bd. 20, 10.11.2020, Nr. 1, date:12.2020: 1-10
|
|
|
|
26277 |
Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis
Enthalten in Nature medicine Bd. 28, 21.7.2022, Nr. 7, date:7.2022: 1455-1460
|
|
|
|
26278 |
Prospects of non-resonant di-Higgs searches and Higgs boson self-coupling measurement at the HE-LHC using machine learning techniques
Enthalten in Journal of high energy physics Bd. 2020, 28.12.2020, Nr. 12, date:12.2020: 1-47
|
|
|
|
26279 |
PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach
Enthalten in Biomed Central (London): BMC Research Notes Bd. 18, 11.3.2025, Nr. 1, date:12.2025: 1-10
|
|
|
|
26280 |
Protecting Machine Learning Models from Training Data Set Extraction
Enthalten in Automatic control and computer sciences Bd. 58, 14.3.2025, Nr. 8, date:12.2024: 1234-1241
|
|
Administration
