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About

Francesco Deodato is a leading figure in radiation oncology, with a research focus that bridges advanced treatment planning and the application of artificial intelligence in cancer care. His major contributions are twofold: pioneering techniques in stereotactic radiosurgery for spinal tumors and developing machine learning models to predict treatment toxicity. His seminal work, "Treatment planning for spinal radiosurgery" (2018), with 35 citations, established foundational protocols for delivering high-precision radiation to complex spinal targets, directly improving patient safety and tumor control. More recently, Deodato spearheaded the ICAROS Study (2025), a multicenter investigation that leverages machine learning to create a predictive model for acute gastrointestinal and genitourinary toxicity in prostate cancer patients undergoing salvage radiotherapy. This work represents a significant leap toward personalized radiotherapy, enabling clinicians to identify high-risk patients and tailor interventions proactively. By integrating computational methods with clinical data, Deodato is shaping a future where radiation oncology is not only more precise but also more predictive, enhancing both treatment outcomes and quality of life for cancer survivors.