Dosimetry, the estimation and assessment of radiation dose received by individuals or materials, is pivotal across many contexts where exposure to ionizing radiation occurs—including medical applications, nuclear industry, and environmental monitoring. Within medical radiation therapy, dosimetry becomes especially critical: accurate calculation of the dose absorbed by tumors ensures effective therapeutic outcomes, while risk to neighboring healthy tissue and medical personnel necessitates stringent control of administered dosage. Complementing dosimetry, particle physics contributes an essential framework for understanding the fundamental constituents of matter and energy, and guides applications that span an extraordinary breadth of contexts—ranging from clinical practice and cancer treatment to space exploration and improving health on Earth. By extending the concepts and principles of particle physics to monitor radiation therapy treatments in real time, automated dosimetry models can furnish on-the-fly measurements of the dose radiated within the patient. These efforts empower medical practitioners to validate the planned dose during the procedure, provide dynamic feedback for modulating temporal delivery characteristics, and underpin precision diagnoses that correlate the dose and biological response.
| Mualliflar | Allawi, Munther bashir Matar, Haeel, Nadia adel Saeed, Ibrahim, Dhuha Sahib Mahdi, Habib, Tabark Mungher Mohi |
|---|---|
| Jurnal | Innovative Multidisciplinary Journal of Applied Technology |
| Nashriyot | ТДТУ Қўқон филиали |
| ISSN | 2995-486X, 2995-486x |
| Nashr sanasi | 2025-09-15 |
| Jild | 3 |
| Son | 9 |
| Betlar | 70-77 |
| Til | Ingliz |
| Indeksga qo‘shilgan | 2026-08-26 |
AI-driven dosimetry, Real-time particle physics simulations, Radiation therapy precision
| APA | Allawi, Munther bashir Matar, Haeel, Nadia adel Saeed, Ibrahim, Dhuha Sahib Mahdi, & Habib, Tabark Mungher Mohi (2025). AI-Driven Dosimetry Using Real-Time Particle Physics Simulations in Radiation Therapy. Innovative Multidisciplinary Journal of Applied Technology, 3(9), 70-77. https://www.multijournals.org/index.php/innovative/article/view/3626 |
|---|---|
| GOST (OAK) | Allawi, Munther bashir Matar va b. AI-Driven Dosimetry Using Real-Time Particle Physics Simulations in Radiation Therapy // Innovative Multidisciplinary Journal of Applied Technology. – 2025. – T. 3, № 9. – P. 70-77. |
| MLA | Allawi, Munther bashir Matar, Haeel, Nadia adel Saeed, Ibrahim, Dhuha Sahib Mahdi, and Habib, Tabark Mungher Mohi. “AI-Driven Dosimetry Using Real-Time Particle Physics Simulations in Radiation Therapy.” Innovative Multidisciplinary Journal of Applied Technology, 3(9), 70-77, 2025. https://www.multijournals.org/index.php/innovative/article/view/3626 |
| Chicago | Allawi, Munther bashir Matar, Haeel, Nadia adel Saeed, Ibrahim, Dhuha Sahib Mahdi, and Habib, Tabark Mungher Mohi. “AI-Driven Dosimetry Using Real-Time Particle Physics Simulations in Radiation Therapy.” Innovative Multidisciplinary Journal of Applied Technology, 3(9), 70-77 (2025). https://www.multijournals.org/index.php/innovative/article/view/3626 |
| Harvard | Allawi, Munther bashir Matar, Haeel, Nadia adel Saeed, Ibrahim, Dhuha Sahib Mahdi, and Habib, Tabark Mungher Mohi (2025) ‘AI-Driven Dosimetry Using Real-Time Particle Physics Simulations in Radiation Therapy’, Innovative Multidisciplinary Journal of Applied Technology, 3(9), 70-77. https://www.multijournals.org/index.php/innovative/article/view/3626 |
| BibTeX | @article{allawimuntherbashirmatar2025,
title = {AI-Driven Dosimetry Using Real-Time Particle Physics Simulations in Radiation Therapy},
author = {Allawi, Munther bashir Matar and Haeel, Nadia adel Saeed and Ibrahim, Dhuha Sahib Mahdi and Habib, Tabark Mungher Mohi},
journal = {Innovative Multidisciplinary Journal of Applied Technology},
year = {2025},
volume = {3},
number = {9},
pages = {70-77},
url = {https://www.multijournals.org/index.php/innovative/article/view/3626}
} |
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