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1 |
Challenges in developing and validating machine learning models for TAVI mortality risk prediction: reply
Leha, Andreas. - Freiburg : Universität, 2024
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2 |
Development and validation of explainable machine learning models for risk of mortality in transcatheter aortic valve implantation: TAVI risk machine scores
Leha, Andreas. - Freiburg : Universität, 2023
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3 |
Does Hepatic Steatosis Influence the Detection Rate of Metastases in the Hepatobiliary Phase of Gadoxetic Acid-Enhanced MRI?
Steffen, Ingo G.. - Leipzig : Universitätsbibliothek Leipzig, 2023
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4 |
Intrinsic dimension adaptive learning rates for kernel methods
Hamm, Thomas. - Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2022
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5 |
Enhancing the differentiation of pulmonary lymphoma and fungal pneumonia in hematological patients using texture analysis in 3-T MRI
Enthalten in European radiology 21.8.2020: 1-11
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6 |
Diagnosis of Left Ventricular Diastolic Dysfunction Using Cardiac Magnetic Resonance Imaging: Comparison of Volume-Time Curves Derived from Long- and Short-Axis Cine Steady-State Free Precession Datasets
Enthalten in RöFo 2020
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7 |
Diagnostic Performance and Reliability of Non-Enhanced Imaging Characterization Quotients for the Differentiation of Infectious and Malignant Pulmonary Nodules in Hematological Patients Using 3T MRI
Enthalten in RöFo 2019
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8 |
Eine lebensstilistische Segmentierung des Jugendmarktes
Hamm, Ingo, 2003
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9 |
CT radiomics to predict Deauville score 4 positive and negative Hodgkin lymphoma manifestations
Enthalten in Scientific reports Bd. 12, 21.11.2022, Nr. 1, date:12.2022: 1-9
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10 |
Effects of parametric feature maps on the reproducibility of radiomics from different fields of view in cardiac magnetic resonance cine images– a clinical and experimental study setting
Enthalten in The international journal of cardiovascular imaging Bd. 41, 23.4.2025, Nr. 6, date:6.2025: 1173-1184
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