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.

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Publication Details

Journal
SHS Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/shsconf/202521401006
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

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

Saad Ouakkas, Maged Ahmed Saleh Abdo, Aziz Boukhair, M. L. Bouhssa et al.
1 citations
SHS Web of Conferences
Radiomics and Machine Learning in Medical Imaging
1.36
article

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

Saad Ouakkas, Maged Ahmed Saleh Abdo, Aziz Boukhair, M. L. Bouhssa, Marya Bouanis, Fatima Ezzahra Arhouni, Mohammed Fahad, Imed Zitouni
article en
1 citations

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.

SHS Web of ConferencesVol. 214
Chouaib Doukkali University (MA)
Openalex Percentile: Top 22%
Radiomics and Machine Learning in Medical Imaging
1.36
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