Rate My Professor Eric Aboagye

Aboagye's research centers on the discovery, development, and translation of molecular imaging methodologies using positron emission tomography, magnetic resonance imaging, and ultrasound to elucidate cancer biology, physiology, pharmacology, therapy response, metabolism (including fatty acid oxidation, glycogenesis, choline, and nucleoside pathways), cell surface receptors for theranostics (such as EGFR, SSTR2, HER2, CXCR4), novel radiotracers, radiomics, and machine learning applications for cancer detection, prognosis, and precision medicine. He pioneered the concept of microdosing in oncology and has led advancements like the Radiomic Prognostic Vector for ovarian cancer prognosis, AI-based virtual biopsy for lung cancer assessment, and PET imaging for glioma and hepatocellular carcinoma outcomes. His contributions include over 450 publications with nearly 19,000 citations and an h-index reflecting substantial impact in the field. Key publications encompass 'Radiotheranostics in oncology: Making precision medicine a reality' (CA: A Cancer Journal for Clinicians, 2023), 'A comparison of machine learning methods for predicting outcomes in hepatocellular carcinoma' (eBioMedicine, 2022), and 'A novel radiotracer to image glycogen metabolism in tumors' (Theranostics, 2014). Aboagye received the first Translational Research Award from the British Association for Cancer Research (2001), the British Institute of Radiology Sir Mackenzie Davidson Medal (2009), and was elected a Fellow of the Academy of Medical Sciences (2010). He holds leadership roles in research committees and contributes to clinical translation of imaging agents.