Deborah Fazzini

Centro Diagnostico Italiano, Università Campus Bio-Medico

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About

Deborah Fazzini is a researcher whose work sits at the intersection of medical imaging and machine learning, with a focused expertise in radiomics for neuro-oncology. Her primary research area is the application of radiomics—the high-throughput extraction of quantitative features from medical images—to improve the prediction and management of acoustic neuroma (vestibular schwannoma), a benign but potentially serious intracranial tumor. Fazzini’s major contributions center on developing predictive models for treatment response to CyberKnife stereotactic radiosurgery, a non-invasive therapy used to control tumor growth. In her most-cited work, "Tackling imbalance radiomics in acoustic neuroma" (2019, 8 citations), she addresses the critical challenge of class imbalance in small radiomics datasets, proposing methods to enhance model reliability. Her earlier pilot studies (2018, 4 citations each) laid the groundwork by demonstrating that radiomic features could predict CyberKnife response, offering a path toward personalized treatment planning. Though her citation counts are modest, Fazzini’s work is notable for tackling a niche clinical problem with advanced computational techniques, bridging the gap between radiology and oncology. Her research holds promise for reducing unnecessary interventions and improving outcomes for patients with this slow-growing tumor.