Area of research
Genetics · Radiology, Nuclear Medicine and Imaging
Research interest
Research focused on Isocitrate dehydrogenase and Cancer imaging, with related work in Precision oncology, Recursive partitioning, Fluid-attenuated inversion recovery. Notable publications include 'Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics', 'AI-based prognostic imaging biomarkers for precision neuro-oncology: the ReSPOND consortium', and 'Radiomics using non-contrast CT to predict hemorrhagic transformation risk in stroke patients undergoing revascularization'.
Radiomics using non-contrast CT to predict hemorrhagic transformation risk in stroke patients undergoing revascularization
Incorporating Supramaximal Resection into Survival Stratification of IDH-wildtype Glioblastoma: A Refined Multi-institutional Recursive Partitioning Analysis
Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study
Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium
Fully automated hybrid approach to predict the<i>IDH</i>mutation status of gliomas via deep learning and radiomics
AI-based prognostic imaging biomarkers for precision neuro-oncology: the ReSPOND consortium