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35421 |
The predictive power of data: machine learning analysis for Covid-19 mortality based on personal, clinical, preclinical, and laboratory variables in a case–control study
Enthalten in BMC infectious diseases Bd. 24, 18.4.2024, Nr. 1, date:12.2024: 1-18
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35422 |
The predictive reframing of machine learning applications: good predictions and bad measurements
Enthalten in European journal for philosophy of science Bd. 12, 26.8.2022, Nr. 3, date:9.2022: 1-21
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35423 |
The predictive role of identifying frailty in assessing the need for palliative care in the elderly: the application of machine learning algorithm
Enthalten in Journal of health, population and nutrition Bd. 44, 23.4.2025, Nr. 1, date:12.2025: 1-13
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35424 |
The predictive value of machine learning for mortality risk in patients with acute coronary syndromes: a systematic review and meta-analysis
Enthalten in European journal of medical research Bd. 28, 20.10.2023, Nr. 1, date:12.2023: 1-13
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35425 |
The Promise of Artificial Intelligence and Machine Learning in Geriatric Anesthesiology Education: An Idea Whose Time Has Come
Enthalten in Current anesthesiology reports Bd. 15, 6.1.2025, Nr. 1, date:12.2025: 1-10
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35426 |
The promise of machine learning applications in solid organ transplantation
Enthalten in npj digital medicine Bd. 5, 11.7.2022, Nr. 1, date:12.2022: 1-13
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35427 |
The promise of machine learning approaches to capture cellular senescence heterogeneity
Enthalten in Nature aging Bd. 4, 26.8.2024, Nr. 9, date:9.2024: 1167-1170
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35428 |
The promise of machine learning models in cardiovascular risk prediction
Enthalten in Internal and emergency medicine Bd. 19, 4.9.2024, Nr. 7, date:10.2024: 1805-1806
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35429 |
The quest for a biological phenotype of adolescent non-suicidal self-injury: a machine-learning approach
Enthalten in Translational Psychiatry Bd. 14, 25.1.2024, Nr. 1, date:12.2024: 1-7
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35430 |
The quest for the reliability of machine learning models in binary classification on tabular data
Enthalten in Scientific reports Bd. 13, 27.10.2023, Nr. 1, date:12.2023: 1-11
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Administration
