Comprehensive Review on the Impact of Artificial Intelligence on Diagnosis and Personalized Treatment in Nuclear Medicine

Artificial intelligence (AI) continues to advance nuclear medicine in all areas, including treatment planning, resource allocation, and precision. The imaging techniques powered by AI enable faster and more accurate diagnosis of diseases and machine learning models improve individual-specific treatment dosimetry. Additionally, AI increases operational efficiency, reduces costs, and lower radiation exposure for patients. Despite these improvements, issues such as ethical concerns, bias in data, and clinical integration difficulties still exist. This review paper discusses the role of AI in changing nuclear medicine practice, emphasizing the pros and cons, and the anticipated future. As the field proves its further value, multidisciplinary collaborations are invited to help ensure AI’s value for future nuclear medicine diagnosis and treatment.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-03-28
DOI
https://doi.org/10.1051/shsconf/202521401006/pdf
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Comprehensive Review on the Impact of Artificial Intelligence on Diagnosis and Personalized Treatment in Nuclear Medicine

Springer Link (Chiba Institute of Technology)
Radiomics and Machine Learning in Medical Imaging
article

Comprehensive Review on the Impact of Artificial Intelligence on Diagnosis and Personalized Treatment in Nuclear Medicine

article en

Abstract

Artificial intelligence (AI) continues to advance nuclear medicine in all areas, including treatment planning, resource allocation, and precision. The imaging techniques powered by AI enable faster and more accurate diagnosis of diseases and machine learning models improve individual-specific treatment dosimetry. Additionally, AI increases operational efficiency, reduces costs, and lower radiation exposure for patients. Despite these improvements, issues such as ethical concerns, bias in data, and clinical integration difficulties still exist. This review paper discusses the role of AI in changing nuclear medicine practice, emphasizing the pros and cons, and the anticipated future. As the field proves its further value, multidisciplinary collaborations are invited to help ensure AI’s value for future nuclear medicine diagnosis and treatment.

Springer Link (Chiba Institute of Technology)
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Openalex Percentile: Top 34%
Radiomics and Machine Learning in Medical Imaging
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