{"ID":2855866,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.12714","arxiv_id":"2510.12714","title":"Artificial intelligence for simplified patient-centered dosimetry in radiopharmaceutical therapies","abstract":"KEY WORDS: Artificial Intelligence (AI), Theranostics, Dosimetry, Radiopharmaceutical Therapy (RPT), Patient-friendly dosimetry KEY POINTS - The rapid evolution of radiopharmaceutical therapy (RPT) highlights the growing need for personalized and patient-centered dosimetry. - Artificial Intelligence (AI) offers solutions to the key limitations in current dosimetry calculations. - The main advances on AI for simplified dosimetry toward patient-friendly RPT are reviewed. - Future directions on the role of AI in RPT dosimetry are discussed.","short_abstract":"KEY WORDS: Artificial Intelligence (AI), Theranostics, Dosimetry, Radiopharmaceutical Therapy (RPT), Patient-friendly dosimetry KEY POINTS - The rapid evolution of radiopharmaceutical therapy (RPT) highlights the growing need for personalized and patient-centered dosimetry. - Artificial Intelligence (AI) offers solutio...","url_abs":"https://arxiv.org/abs/2510.12714","url_pdf":"https://arxiv.org/pdf/2510.12714v1","authors":"[\"Alejandro Lopez-Montes\",\"Fereshteh Yousefirizi\",\"Yizhou Chen\",\"Yazdan Salimi\",\"Robert Seifert\",\"Ali Afshar-Oromieh\",\"Carlos Uribe\",\"Axel Rominger\",\"Habib Zaidi\",\"Arman Rahmim\",\"Kuangyu Shi\"]","published":"2025-10-14T16:55:36Z","proceeding":"physics.med-ph","tasks":"[\"physics.med-ph\",\"cs.AI\",\"physics.app-ph\"]","methods":"[]","has_code":false}