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Ergebnis der Suche nach:
"Machine Learning"
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25841 - 25850 von 29259
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25841
Predicting Packaging Sizes Using Machine Learning
Enthalten in Operations research forum Bd. 3, 22.8.2022, Nr. 3, date:9.2022: 1-14
25842
Predicting particulate matter (PM2.5) air pollution levels in Almaty city using machine learning techniques
Enthalten in Modeling earth systems and environment Bd. 11, 28.4.2025, Nr. 4, date:8.2025: 1-15
25843
Predicting pathologic complete response in locally advanced rectal cancer patients after neoadjuvant therapy: a machine learning model using XGBoost
Enthalten in International journal of colorectal disease Bd. 37, 15.6.2022, Nr. 7, date:7.2022: 1621-1634
25844
Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach
Enthalten in Breast cancer research Bd. 26, 29.10.2024, Nr. 1, date:12.2024: 1-12
25845
Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer patients: use of MRI radiomics data from three regions with multiple machine learning algorithms
Enthalten in Journal of cancer research and clinical oncology Bd. 150, 21.3.2024, Nr. 3, date:3.2024: 1-13
25846
Predicting pathological highly invasive lung cancer from preoperative [18F]FDG PET/CT with multiple machine learning models
Enthalten in European journal of nuclear medicine and molecular imaging Bd. 50, 17.11.2022, Nr. 3, date:2.2023: 715-726
25847
Predicting Patient Hospital Charges Using Machine Learning
Enthalten in Radioelectronics and communications systems Bd. 65, 7.2.2024, Nr. 12, date:12.2022: 665-673
25848
Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach
Enthalten in BMC medical informatics and decision making Bd. 20, 6.2.2020, Nr. 1, date:12.2020: 1-9
25849
Predicting patient-reported outcome of activities of daily living in stroke rehabilitation: a machine learning study
Enthalten in Journal of neuroEngineering and rehabilitation Bd. 20, 23.2.2023, Nr. 1, date:12.2023: 1-12
25850
Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning
Enthalten in BMC medical informatics and decision making Bd. 19, 8.1.2019, Nr. 1, date:12.2019: 1-13
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