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25981 |
Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment
Enthalten in La Radiologia medica Bd. 128, 11.9.2023, Nr. 11, date:11.2023: 1310-1332
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25982 |
Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR
Enthalten in Journal of translational medicine Bd. 19, 24.10.2021, Nr. 1, date:12.2021: 1-10
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25983 |
Radiomics-based machine learning methods for isocitrate dehydrogenase genotype prediction of diffuse gliomas
Enthalten in Journal of cancer research and clinical oncology Bd. 145, 4.2.2019, Nr. 3, date:3.2019: 543-550
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25984 |
Radiomics-based machine learning (ML) classifier for detection of type 2 diabetes on standard-of-care abdomen CTs: a proof-of-concept study
Enthalten in Abdominal radiology Bd. 47, 10.9.2022, Nr. 11, date:11.2022: 3806-3816
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25985 |
Radiomics-based machine learning model for diagnosing internal abdominal hernias: a retrospective study
Enthalten in Scientific reports Bd. 15, 22.5.2025, Nr. 1, date:12.2025: 1-9
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25986 |
Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest
Enthalten in Scientific reports Bd. 12, 14.6.2022, Nr. 1, date:12.2022: 1-13
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25987 |
Radiomics based on readout-segmented echo-planar imaging (RS-EPI) diffusion-weighted imaging (DWI) for prognostic risk stratification of patients with rectal cancer: a two-centre, machine learning study using the framework of predictive, preventive, and personalized medicine
Enthalten in European Association for Predictive, Preventive and Personalised Medicine: The EPMA journal Bd. 13, 12.11.2022, Nr. 4, date:12.2022: 633-647
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25988 |
Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques
Enthalten in Cancer imaging Bd. 20, 5.8.2020, Nr. 1, date:12.2020: 1-13
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25989 |
Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study
Enthalten in Journal of cardiothoracic surgery Bd. 20, 11.2.2025, Nr. 1, date:12.2025: 1-9
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25990 |
Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules
Enthalten in European radiology Bd. 30, 23.8.2019, Nr. 1, date:1.2020: 558-570
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