Patrick Duhanxhiu
Papers
1
Total Citations
3
H-Index
1
About
Patrick Duhanxhiu is a researcher at the forefront of applying machine learning to radiation oncology, with a primary focus on improving treatment outcomes for prostate cancer patients. His most cited work, the ICAROS Study (2025), represents a significant contribution to personalized medicine in oncology. In this multicenter investigation, Duhanxhiu and his team developed a machine learning-based predictive model to forecast acute gastrointestinal and genitourinary toxicity in prostate cancer patients undergoing salvage radiotherapy after prostatectomy. By identifying key prognostic factors through advanced computational techniques, his model enables clinicians to better anticipate and mitigate treatment side effects, thereby enhancing patient quality of life. This work, already garnering early citations, underscores Duhanxhiu’s commitment to translating complex data into actionable clinical tools. His research sits at the intersection of artificial intelligence and radiation therapy, demonstrating how predictive analytics can refine treatment planning and reduce toxicity risks. As an emerging voice in the field, Duhanxhiu’s contributions are paving the way for more precise, patient-tailored cancer care, making him a researcher to watch in the evolving landscape of oncological informatics.
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Top Papers
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