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Systematic Review

Artificial Intelligence-Based Software as a Medical Device (AI-SaMD): A Systematic Review

1
Center for Scientific Research and Entrepreneurship, Northern Border University, Arar 73213, Saudi Arabia
2
Department of Computer Science, Faculty of Science, Northern Border University, Arar 73213, Saudi Arabia
3
Applied College, Northern Border University, Arar 73213, Saudi Arabia
*
Author to whom correspondence should be addressed.
Healthcare 2025, 13(7), 817; https://doi.org/10.3390/healthcare13070817 (registering DOI)
Submission received: 10 March 2025 / Revised: 28 March 2025 / Accepted: 31 March 2025 / Published: 3 April 2025
(This article belongs to the Special Issue Artificial Intelligence in Healthcare: Opportunities and Challenges)

Abstract

Background/Objectives: Artificial intelligence-based software as a medical device (AI-SaMD) refers to AI-powered software used for medical purposes without being embedded in physical devices. Despite increasing approvals over the past decade, research in this domain—spanning technology, healthcare, and national security—remains limited. This research aims to bridge the existing research gap in AI-SaMD by systematically reviewing the literature from the past decade, with the aim of classifying key findings, identifying critical challenges, and synthesizing insights related to technological, clinical, and regulatory aspects of AI-SaMD. Methods: A systematic literature review based on the PRISMA framework was performed to select the relevant AI-SaMD studies published between 2015 and 2024 in order to uncover key themes such as publication venues, geographical trends, key challenges, and research gaps. Results: Most studies focus on specialized clinical settings like radiology and ophthalmology rather than general clinical practice. Key challenges to implement AI-SaMD include regulatory issues (e.g., regulatory frameworks), AI malpractice (e.g., explainability and expert oversight), and data governance (e.g., privacy and data sharing). Existing research emphasizes the importance of (1) addressing the regulatory problems through the specific duties of regulatory authorities, (2) interdisciplinary collaboration, (3) clinician training, (4) the seamless integration of AI-SaMD with healthcare software systems (e.g., electronic health records), and (5) the rigorous validation of AI-SaMD models to ensure effective implementation. Conclusions: This study offers valuable insights for diverse stakeholders, emphasizing the need to move beyond theoretical analyses and prioritize practical, experimental research to advance the real-world application of AI-SaMDs. This study concludes by outlining future research directions and emphasizing the limitations of the predominantly theoretical approaches currently available.
Keywords: AI; SaMD; AI-SaMD; regulatory; systematic review AI; SaMD; AI-SaMD; regulatory; systematic review

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MDPI and ACS Style

Ebad, S.A.; Alhashmi, A.; Amara, M.; Miled, A.B.; Saqib, M. Artificial Intelligence-Based Software as a Medical Device (AI-SaMD): A Systematic Review. Healthcare 2025, 13, 817. https://doi.org/10.3390/healthcare13070817

AMA Style

Ebad SA, Alhashmi A, Amara M, Miled AB, Saqib M. Artificial Intelligence-Based Software as a Medical Device (AI-SaMD): A Systematic Review. Healthcare. 2025; 13(7):817. https://doi.org/10.3390/healthcare13070817

Chicago/Turabian Style

Ebad, Shouki A., Asma Alhashmi, Marwa Amara, Achraf Ben Miled, and Muhammad Saqib. 2025. "Artificial Intelligence-Based Software as a Medical Device (AI-SaMD): A Systematic Review" Healthcare 13, no. 7: 817. https://doi.org/10.3390/healthcare13070817

APA Style

Ebad, S. A., Alhashmi, A., Amara, M., Miled, A. B., & Saqib, M. (2025). Artificial Intelligence-Based Software as a Medical Device (AI-SaMD): A Systematic Review. Healthcare, 13(7), 817. https://doi.org/10.3390/healthcare13070817

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