|
25901 |
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
|
|
|
|
25902 |
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
|
|
|
|
25903 |
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
|
|
|
|
25904 |
Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning
Enthalten in Cardiovascular diabetology Bd. 23, 26.11.2024, Nr. 1, date:12.2024: 1-15
|
|
|
|
25905 |
Prognostic value of texture analysis from cardiac magnetic resonance imaging in patients with Takotsubo syndrome: a machine learning based proof-of-principle approach
Enthalten in Scientific reports Bd. 10, 25.11.2020, Nr. 1, date:12.2020: 1-9
|
|
|
|
25906 |
Prognostication and Risk Factors for Cystic Fibrosis via Automated Machine Learning
Enthalten in Scientific reports Bd. 8, 26.7.2018, Nr. 1, date:12.2018: 1-19
|
|
|
|
25907 |
Prognostics and Health Management of Electronics: Fundamentals, Machine Learning, and the Internet of Things
Enthalten in Life cycle reliability and safety engineering Bd. 9, 20.3.2020, Nr. 2, date:6.2020: 225-226
|
|
|
|
25908 |
Progress on climate action: a multilingual machine learning analysis of the global stocktake
Enthalten in Climatic change Bd. 176, 8.12.2023, Nr. 12, date:12.2023: 1-12
|
|
|
|
25909 |
Progresses and Challenges of Machine Learning Approaches in Thermochemical Processes for Bioenergy: A Review
Enthalten in The Korean journal of chemical engineering Bd. 41, 10.5.2024, Nr. 7, date:7.2024: 1923-1953
|
|
|
|
25910 |
Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection
Enthalten in Health Information Science and Systems Bd. 5, 27.9.2017, Nr. 1, date:12.2017: 1-21
|
|
Administration
