RAPTOR-AI: An open-source AI powered radiation protection toolkit for radioisotopes

Hiroshi Watabe; Peter K N Yu; Dragana Krstic; Dragoslav Nikezic; Kyeong Min Kim; Taiga Yamaya; Naoki Kawachi; Hiroki Tanaka; Zoran Jovanovic; A K F Haque; M Rafiqul Islam; Gary Tse; Quinncy Lee; Mehrdad Shahmohammadi Beni

doi:10.1016/j.apradiso.2025.111797

RAPTOR-AI: An open-source AI powered radiation protection toolkit for radioisotopes

Appl Radiat Isot. 2025 Jul:221:111797. doi: 10.1016/j.apradiso.2025.111797. Epub 2025 Mar 28.

Authors

Affiliations

¹ Division of Radiation Protection and Nuclear Safety Research Center for Accelerator and Radioisotope Science, Tohoku University, 6-3 Aoba, Aramaki, Aoba, Sendai, 980-8578 Miyagi, Japan.
² Department of Physics, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong, China.
³ Faculty of Science, University of Kragujevac, R. Domanovica 12, 34000, Kragujevac, Serbia.
⁴ Korea Institute of Radiological & Medical Sciences, 75, Nowon-ro, Nowon-gu, Seoul, Republic of Korea.
⁵ National Institutes for Quantum Science and Technology, Anagawa 4-9-1, Inage-ku, Chiba-shi, Chiba 263-8555, Japan.
⁶ National Institutes for Quantum Science and Technology, 1233 Watanuki, Takasaki, Gunma 370 1292, Japan.
⁷ Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashiro-Nishi, Kumatori-cho, Sennan-gun, Osaka 590-0494, Japan.
⁸ State University of Novi Pazar Department of Natural Science and Mathematics, Vuka Karadzica 9, 36300, Novi Pazar, Serbia.
⁹ Atomic and Molecular Physics Laboratory, Department of Physics, University of Rajshahi, Rajshahi 6205, Bangladesh.
¹⁰ Institute of Nuclear Medical Physics, AERE, Bangladesh Atomic Energy Commission, Dhaka, 1349, Bangladesh.
¹¹ School of Nursing and Health Studies, Hong Kong Metropolitan University, Homantin, Kowloon, Hong Kong, China.
¹² The Institute of Applied Health Sciences, The School of Medicine, Medical Sciences, and Nutrition, University of Aberdeen, Aberdeen, United Kingdom; Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
¹³ Division of Radiation Protection and Nuclear Safety Research Center for Accelerator and Radioisotope Science, Tohoku University, 6-3 Aoba, Aramaki, Aoba, Sendai, 980-8578 Miyagi, Japan; Department of Physics, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong, China; School of Nursing and Health Studies, Hong Kong Metropolitan University, Homantin, Kowloon, Hong Kong, China. Electronic address: ben.sh@tohoku.ac.jp.

PMID: 40184907
DOI: 10.1016/j.apradiso.2025.111797

Abstract

Artificial intelligence (AI) has gained significant attention in various scientific fields due to its ability to process large datasets. In nuclear radiation physics, while AI presents exciting opportunities, it cannot replace physics-based models essential for explaining radiation interactions with matter. To combine the strengths of both, we have developed and open-sourced the Radiation Protection Toolkit for Radioisotopes with Artificial Intelligence (RAPTOR-AI). This toolkit integrates AI with the Particle and Heavy Ion Transport code System (PHITS) Monte Carlo package, enabling rapid radiation protection analysis for radioisotopes and structural shielding. RAPTOR-AI is particularly valuable for emergency scenarios, allowing quick dose dispersion assessments when a facility's structural map is available, enhancing safety and response efficiency.

Keywords: Artificial intelligence; Monte Carlo method; Nuclear radiation; Open-source; Radiation protection.

MeSH terms

Artificial Intelligence*
Humans
Monte Carlo Method
Radiation Protection* / methods
Radioisotopes* / analysis

Substances

Radioisotopes