Background/Objectives: Artificial Intelligence (AI) is becoming increasingly important in Medicine. The aim of this review is to summarize its use in the field of Nuclear Cardiology. Methods: First, we provide a short description of how AI works. Then we performed a review of the literature focusing on the articles in which AI is used for image interpretation for diagnostic or prognostic purposes. Results: AI has been applied according to various approaches for both diagnosis and prognosis. The achieved gains have been so far relatively limited as compared to traditional methodologies. However, promising results have been reported, including interesting perspectives for the explainability of AI results and their potential integration in clinical routine. Conclusions: AI is soon going to play an important role in Nuclear Cardiology, but further improvements are needed to reach significant gains in terms of diagnostic accuracy, and prospective studies on its prognostic capabilities are still lacking. Furthermore, several important issues must be solved, such as availability and feasibility within the processing workflow, explainability, liability, and ethics of its application in clinical decision-making.
Artificial Intelligence in Nuclear Cardiology / Sciagra, Roberto; Valente, Samuele; Dominietto, Marco. - In: JOURNAL OF CLINICAL MEDICINE. - ISSN 2077-0383. - ELETTRONICO. - 14:(2025), pp. 6416.0-6416.0. [10.3390/jcm14186416]
Artificial Intelligence in Nuclear Cardiology
Sciagra, Roberto;Valente, Samuele;
2025
Abstract
Background/Objectives: Artificial Intelligence (AI) is becoming increasingly important in Medicine. The aim of this review is to summarize its use in the field of Nuclear Cardiology. Methods: First, we provide a short description of how AI works. Then we performed a review of the literature focusing on the articles in which AI is used for image interpretation for diagnostic or prognostic purposes. Results: AI has been applied according to various approaches for both diagnosis and prognosis. The achieved gains have been so far relatively limited as compared to traditional methodologies. However, promising results have been reported, including interesting perspectives for the explainability of AI results and their potential integration in clinical routine. Conclusions: AI is soon going to play an important role in Nuclear Cardiology, but further improvements are needed to reach significant gains in terms of diagnostic accuracy, and prospective studies on its prognostic capabilities are still lacking. Furthermore, several important issues must be solved, such as availability and feasibility within the processing workflow, explainability, liability, and ethics of its application in clinical decision-making.| File | Dimensione | Formato | |
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