Elisabeth Pfaehler
Papers
1
Total Citations
135
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1
About
Elisabeth Pfaehler is a leading researcher in the field of medical imaging and radiomics, with a primary focus on advancing quantitative analysis in oncology, particularly for prostate cancer. Her work bridges machine learning and nuclear medicine to improve non-invasive disease characterization. In her landmark 2020 study, which has garnered 135 citations, she demonstrated how machine learning-based analysis of [18F]DCFPyL PET radiomics can effectively stratify risk in primary prostate cancer patients. This contribution is pivotal, as it moves beyond conventional visual interpretation toward objective, data-driven risk assessment using quantitative PSMA PET metrics. By integrating advanced computational methods with molecular imaging, Pfaehler has helped pave the way for more personalized treatment planning. Her research not only enhances the prognostic power of PET imaging but also underscores the potential of radiomics to extract hidden biomarkers from standard clinical scans. With her work cited extensively, Pfaehler is recognized as a key figure in the evolution of precision oncology, where artificial intelligence and imaging converge to improve patient outcomes. Her ongoing efforts continue to shape how clinicians leverage quantitative imaging for cancer management.
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