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25561 |
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
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25562 |
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
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25563 |
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
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25564 |
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
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25565 |
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
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25566 |
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
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25567 |
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
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25568 |
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
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25569 |
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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25570 |
Predicting peak inundation depths with a physics informed machine learning model
Enthalten in Scientific reports Bd. 14, 27.6.2024, Nr. 1, date:12.2024: 1-12
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