Ethical and regulatory challenges of AI technologies in healthcare: A narrative review

Mennella, Ciro; Maniscalco, Umberto; De Pietro, Giuseppe; Esposito, Massimo

doi:10.1016/j.heliyon.2024.e26297

Cited by 32 publications

(7 citation statements)

References 76 publications

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“…Challenges and future directions in AI and ML in laparoscopic surgery encompass a range of considerations, including ethical concerns, transparency issues, workforce implications, and regulatory frameworks [4]. One prominent challenge revolves around the ethical implications of data privacy and security in the context of AI-and ML-driven surgical technologies.…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

Partnering With Technology: Advancing Laparoscopy With Artificial Intelligence and Machine Learning

Reza,

Bokhari

2024

Cureus

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Artificial intelligence (AI) and machine learning (ML) have emerged as transformative technologies in optimizing laparoscopic surgery, offering innovative solutions to enhance surgical precision, efficiency, and safety. This editorial explores the potential role of AI/ML across the surgical continuum, including preoperative optimization, intraoperative assistance, and postoperative care. It outlines the benefits of laparoscopic surgery compared to traditional open procedures and identifies current challenges such as technical difficulty and human error. The editorial discusses how AI and ML technologies can address these challenges, including patient selection and risk stratification, surgical planning and simulation, and personalized medicine approaches. Moreover, it examines the role of AI/ML in intraoperative assistance, such as instrument tracking and guidance, real-time tissue analysis, and the detection of potential complications. Postoperative care and follow-up are also explored, highlighting the potential of AI/ML in monitoring patient recovery, predicting and preventing complications, and tailoring rehabilitation plans. Ethical concerns surrounding data privacy and security, the lack of transparency in decision-making, potential job displacement, and regulatory frameworks are discussed as challenges to the widespread adoption of AI/ML in laparoscopic surgery. Finally, potential areas for further research and exploration are outlined, emphasizing interdisciplinary collaboration and the need for transparent and accountable AI systems. Overall, this editorial provides insights into the challenges and opportunities in harnessing AI/ML technologies to optimize laparoscopic surgery and improve patient outcomes.

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Section: Challenges and Future Directionsmentioning

confidence: 99%

Partnering With Technology: Advancing Laparoscopy With Artificial Intelligence and Machine Learning

Reza,

Bokhari

2024

Cureus

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“…Blockchain technology can significantly enhance data integrity and transparency by providing an immutable ledger that logs all data transactions, facilitating traceability and minimizing inconsistencies. Robust data management practices are required to maintain datasets' accuracy, cleanliness, and organization, including data normalization, eliminating duplicate records, and continual updates to keep datasets comprehensive and current [62]. These measures are foundational for effectively integrating AI technologies with existing healthcare data systems and building predictive models on reliable data foundations.…”

Section: Operational Efficiency and Predictive Analytics In Healthcar...mentioning

confidence: 99%

AI-Driven Healthcare in France

2024

IJFMR

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This integrative literature review (ILR) looks into the use of artificial intelligence (AI) technology in the French healthcare system, emphasizing personalized medicine and predictive health analytics. The study subject is the problematic integration of AI technologies, which is hampered by significant challenges, including data privacy concerns, system interoperability, ethical and legal issues, resistance to technological change, and the need for extensive training of healthcare professionals. These issues affect French healthcare professionals and politicians, who must overcome these challenges to utilize AI's potential fully. This research aims to investigate and assess the integration of AI into the French healthcare system, particularly in personalized medicine and predictive health analytics, to identify and address the obstacles and leverage the opportunities that improve patient care and operational efficiency. The ILR's guiding conceptual framework is based on three essential concepts: artificial intelligence, personalized medicine, and predictive healthcare analytics. The research methodology consists in thoroughly examining current literature, qualitative study of case studies, and interviews with industry professionals. The study's findings show that AI has tremendous potential to increase diagnostic precision and treatment accuracy in the French healthcare system. They highlight initiatives such as establishing specialized departments like "Intelligent Healthcare Services" and creating positions like "Intelligent Doctor". The conclusions address the potential implications of the findings for enhancing patient care and operational efficiency, as well as recommendations for further study and practice. These include performing longitudinal studies, looking into emerging data integrity solutions such as blockchain, and improving healthcare professional training programs. Ultimately, breaking down current obstacles and ensuring that AI technologies improve healthcare delivery and patient outcomes would make France a leader in AI-driven medical innovation.

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“…Regulatory and ethical considerations add another layer of complexity. Healthcare AI tools must comply with various regulatory requirements, such as data privacy laws and medical device regulations [23,24]. Ethical use of AI in healthcare, including informed consent, data security, and accountability, is crucial to protect patient rights and safety [24].…”

Section: Challenges Of Implementing Ai In Healthcare For Blood Pressu...mentioning

confidence: 99%

AI-Enhanced Health Tools for Revolutionizing Hypertension Management and Blood Pressure Control

Faezi,

Alinezhad

2024

InfoScience Trends

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Ethical and regulatory challenges of AI technologies in healthcare: A narrative review

Cited by 32 publications

References 76 publications

Partnering With Technology: Advancing Laparoscopy With Artificial Intelligence and Machine Learning

Partnering With Technology: Advancing Laparoscopy With Artificial Intelligence and Machine Learning

AI-Driven Healthcare in France

AI-Enhanced Health Tools for Revolutionizing Hypertension Management and Blood Pressure Control

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