• Kawahara D, Tsuneda M, Ozawa S, Okamoto H, Nakamura M, Nishio T, Saito A, Nagata Y., "Stepwise deep neural network (stepwise-net) for head and neck auto-segmentation on CT images", Comput Biol Med., 143, 105295 (2022). DOI
   
• Kawahara D, Tang X, Lee CL, et al., "Predicting the local response of metastatic brain tumor to Gamma Knife radiosurgery by radiomics with a machine learning method", Front Oncol., 10, 569461 (2021). DOI
   
• Kawahara D, Wu L, Watanabe Y., "Optimization of irradiation interval for fractionated stereotactic radiosurgery by a cellular automata model with reoxygenation effects", Phys Med Biol., 65(8), 085008 (2020). DOI

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Born in Yamaguchi, Dr. Kawahara attended Kumamoto University, and after graduating in 2010, he worked as a radiological technologist at Hiroshima University Hospital. While gaining clinical experience, he pursued his postgraduate studies at Hiroshima University and subsequently acquired a degree. From 2018, he also spent a year in the USA studying at the University of Minnesota. Since returning to Japan in 2019, he has been engaged in clinical practice as an assistant professor/medical physicist in the Division of Clinical Radiology at Hiroshima University Hospital, where he has published many research theses on the topic of AI in healthcare.

As the development of AI technology is accelerating, research on AI for medical diagnosis and prognosis prediction has been undertaken in the medical field. However, the current AI technology has not yet reached the level where it can analyze what is occurring inside of the body if a patient receives a poor initial prognosis using AI. Therefore, Dr. Kawahara is working on developing a system which allows AI to analyze prognosis factors to identify the optimum treatment. Once AI becomes commonly utilized in such a way, it will enormously reduce the cost and time taken to suggest new treatments in basic research and clinical trials, which is expected to make significant contributions to medical development.