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16211 |
Use machine learning to predict pulmonary metastasis of esophageal cancer: a population-based study
Enthalten in Journal of cancer research and clinical oncology Bd. 150, 16.9.2024, Nr. 9, date:9.2024: 1-10
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16212 |
Use machine learning to predict treatment outcome of early childhood caries
Enthalten in BMC oral health Bd. 25, 15.3.2025, Nr. 1, date:12.2025: 1-9
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16213 |
Use of artificial intelligence for public health surveillance: a case study to develop a machine Learning-algorithm to estimate the incidence of diabetes mellitus in France
Enthalten in Archives of public health Bd. 79, 22.9.2021, Nr. 1, date:12.2021: 1-13
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16214 |
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Enthalten in BMC bioinformatics Bd. 9, 18.11.2008, Nr. 1, date:12.2008: 1-12
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16215 |
Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy
Enthalten in Supportive care in cancer Bd. 33, 13.2.2025, Nr. 3, date:3.2025: 1-10
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16216 |
Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis
Enthalten in Molecular medicine Bd. 29, 20.3.2023, Nr. 1, date:12.2023: 1-16
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16217 |
Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population
Enthalten in BMC pulmonary medicine Bd. 22, 29.8.2022, Nr. 1, date:12.2022: 1-11
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|
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16218 |
Use of machine learning techniques for identifying ischemic stroke instead of the rule-based methods: a nationwide population-based study
Enthalten in European journal of medical research Bd. 29, 3.1.2024, Nr. 1, date:12.2024: 1-9
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|
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16219 |
Use of machine learning techniques to identify HIV predictors for screening in sub-Saharan Africa
Enthalten in BMC medical research methodology Bd. 21, 31.7.2021, Nr. 1, date:12.2021: 1-11
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|
16220 |
Use of machine learning to analyse routinely collected intensive care unit data: a systematic review
Enthalten in Critical care Bd. 23, 22.8.2019, Nr. 1, date:12.2019: 1-11
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Administration
