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3. CCTA-derived functional and morphological features and their comparative performance in predicting impaired coronary vasodilatation by PET-myocardial perfusion imaging. (8th February 2021)

4. Coronary CT angiography derived features for predicting an abnormal pet myocardial perfusion imaging: a machine learning approach. (25th November 2020)

5. Elevated triglycerides and low HDL cholesterol predict coronary heart disease risk in patients with stable angina. (20th July 2021)

6. Prediction of impaired myocardial blood flow (MBF) with the use of machine learning techniques on CTCA based parameters. (8th February 2021)

7. Radiomics-based analysis by machine learning techniques improves characterization of functionally significant coronary lesions. (3rd October 2022)

8. Relationship between endothelial shear stress, plaque burden and stenosis severity and their comparative performance in predicting impaired coronary vasodilation by pet myocardial perfusion imaging. (25th November 2020)

9. Silent cerebral embolisation during TAVI: evolution, predictors and neurocognitive effects. (25th November 2020)