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About

Si Yeol Song is a leading figure in Korean oncology and medical physics, whose work bridges the critical gap between clinical cancer care and advanced radiation therapy technology. His research primarily focuses on lung cancer epidemiology and the development of innovative motion management techniques for precision radiotherapy. Song’s landmark study, "Lung Cancer in Korea" (2021, 11 citations), provides a comprehensive epidemiological analysis that has become a foundational reference for understanding regional cancer patterns and guiding public health strategies. In parallel, his pioneering engineering work, "Geometric and dosimetric verification of a recurrent neural network algorithm to compensate for respiratory motion using an articulated robotic couch" (2020, 10 citations), demonstrates a novel integration of artificial intelligence with robotic treatment delivery. This contribution addresses one of radiotherapy’s most persistent challenges—accounting for tumor movement during breathing—by validating a deep learning approach that enhances targeting accuracy and reduces harm to healthy tissue. Through these dual contributions, Song exemplifies the modern translational researcher, using computational innovation to solve real-world clinical problems while also shaping the epidemiological landscape of cancer care in Korea.