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25821 |
Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors
Enthalten in Journal of computer aided molecular design Bd. 33, 19.11.2019, Nr. 11, date:11.2019: 965-971
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25822 |
Prediction of p53 mutation status in rectal cancer patients based on magnetic resonance imaging-based nomogram: a study of machine learning
Enthalten in Cancer imaging Bd. 23, 18.9.2023, Nr. 1, date:12.2023: 1-11
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25823 |
Prediction of patent grant and interpreting the key determinants: an application of interpretable machine learning approach
Enthalten in Scientometrics Bd. 128, 22.6.2023, Nr. 9, date:9.2023: 4933-4969
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25824 |
Prediction of pathologic complete response to neoadjuvant chemotherapy using machine learning models in patients with breast cancer
Enthalten in Breast cancer research and treatment Bd. 189, 5.7.2021, Nr. 3, date:10.2021: 747-757
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25825 |
Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis
Enthalten in BMC cancer Bd. 19, 17.5.2019, Nr. 1, date:12.2019: 1-12
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25826 |
Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms
Enthalten in European journal of medical research Bd. 30, 13.3.2025, Nr. 1, date:12.2025: 1-12
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25827 |
Prediction of Periventricular Leukomalacia in Neonates after Cardiac Surgery Using Machine Learning Algorithms
Enthalten in Journal of medical systems Bd. 42, 17.8.2018, Nr. 10, date:10.2018: 1-11
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25828 |
Prediction of persistent acute kidney injury in postoperative intensive care unit patients using integrated machine learning: a retrospective cohort study
Enthalten in Scientific reports Bd. 12, 12.10.2022, Nr. 1, date:12.2022: 1-11
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25829 |
Prediction of Physical Properties of Double Halides Using Machine Learning Methods
Enthalten in Pattern recognition and image analysis Bd. 34, 17.10.2024, Nr. 3, date:9.2024: 819-830
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25830 |
Prediction of physical properties of thermosetting resin by using machine learning and structural formulas of raw materials
Enthalten in MRS advances Bd. 5, 27.9.2020, Nr. 29-30, date:6.2020: 1567-1575
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