The future regulation of artificial intelligence systems in healthcare services and medical research in the European Union

Mészáros, János; Minari, Jusaku; Huys, Isabelle

doi:10.3389/fgene.2022.927721

Cited by 39 publications

(18 citation statements)

References 25 publications

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“…Experts differ in their opinions on the importance of the interpretability associated with white-box modelling and the superiority of black-box deep learning for complex tasks that may be constrained by an insistence on interpretability or, indeed, by the misunderstanding that may occur as a result of enforced explainability [37,38]. These controversies aside, current guidelines typically require that any AI component involved in healthcare or health-related research be transparent and explainable, and upcoming EU legislation is expected to formalize this into law [39,40]. The AI method under evaluation in this study is considered transparent and explainable, in line with these current guidelines and proposed future legislation.…”

Section: Discussionmentioning

confidence: 99%

CLASSICA: Validating artificial intelligence in classifying cancer in real time during surgery

Moynihan,

Hardy,

Dalli

et al. 2023

Colorectal Disease

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AimTreatment pathways for significant rectal polyps differ depending on the underlying pathology, but pre‐excision profiling is imperfect. It has been demonstrated that differences in fluorescence perfusion signals following injection of indocyanine green (ICG) can be analysed mathematically and, with the assistance of artificial intelligence (AI), used to classify tumours endoscopically as benign or malignant. This study aims to validate this method of characterization across multiple clinical sites regarding its generalizability, usability and accuracy while developing clinical‐grade software to enable it to become a useful method.MethodsThe CLASSICA study is a prospective, unblinded multicentre European observational study aimed to validate the use of AI analysis of ICG fluorescence for intra‐operative tissue characterization. Six hundred patients undergoing transanal endoscopic evaluation of significant rectal polyps and tumours will be enrolled in at least five clinical sites across the European Union over a 4‐year period. Video recordings will be analysed regarding dynamic fluorescence patterns centrally as software is developed to enable analysis with automatic classification to happen locally. AI‐based classification and subsequently guided intervention will be compared with the current standard of care including biopsies, final specimen pathology and patient outcomes.DiscussionCLASSICA will validate the use of AI in the analysis of ICG fluorescence for the purposes of classifying significant rectal polyps and tumours endoscopically. Follow‐on studies will compare AI‐guided targeted biopsy or, indeed, AI characterization alone with traditional biopsy and AI‐guided local excision versus traditional excision with regard to marginal clearance and recurrence.

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Section: Discussionmentioning

confidence: 99%

CLASSICA: Validating artificial intelligence in classifying cancer in real time during surgery

Moynihan,

Hardy,

Dalli

et al. 2023

Colorectal Disease

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“…Its provisions on automated decision-making and profiling could potentially apply to AI systems, but the regulation does not provide specific guidance on how these provisions should be interpreted in the context of AI and LLMs. 34 In addition to the European Union, currently, at least 69 countries and territories have already implemented more than 800 AI policy initiatives. 19 While the European Union has enacted the comprehensive EU AI Act, other countries, such as the United States (US), have opted for nonbinding guidelines instead, thereby adopting a more flexible approach to AI regulation.…”

Section: Explainable Aimentioning

confidence: 99%

“…The GDPR, while providing robust data protection measures, does not directly address the use of AI and LLMs in clinical pharmacology. Its provisions on automated decision‐making and profiling could potentially apply to AI systems, but the regulation does not provide specific guidance on how these provisions should be interpreted in the context of AI and LLMs 34 …”

Section: Mitigation Measuresmentioning

confidence: 99%

Artificial intelligence in clinical pharmacology: A case study and scoping review of large language models and bioweapon potential

Rubinic,

Kurtov,

Rubinic

et al. 2023

Brit J Clinical Pharma

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AimThis paper aims to explore the possibility of employing large language models (LLMs) – a type of artificial intelligence (AI) – in clinical pharmacology, with a focus on its possible misuse in bioweapon development. Additionally, ethical considerations, legislation, and potential risk reduction measures are analysed.MethodsA comprehensive review of existing literature investigates the potential misuse of AI and LLMs in bioweapon creation. The search includes articles from PubMed, Scopus, and Web of Science Core Collection that were identified using a specific protocol. To explore the regulatory landscape, the OECD.ai platform was used.Resultshe review highlights the dual‐use vulnerability of AI and LLMs, with a focus on bioweapon development. Subsequently, a case study is used to illustrate the potential of AI manipulation resulting in harmful substance synthesis. Existing regulations inadequately address the ethical concerns tied to AI and LLMs. Mitigation measures are proposed, including technical solutions (explainable AI), establishing ethical guidelines through collaborative efforts, and implementing policy changes to create a comprehensive regulatory framework.ConclusionThe integration of AI and LLMs into clinical pharmacology presents invaluable opportunities, while also introducing significant ethical and safety considerations. Addressing the dual‐use nature of AI requires robust regulations, as well as adopting a strategic approach grounded in technical solutions and ethical values following the principles of transparency, accountability, and safety. Additionally, AI’s potential role in developing countermeasures against novel hazardous substances is underscored. By adopting a proactive approach, the potential benefits of AI and LLMs can be fully harnessed while minimizing the associated risks.

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“…31 On the other hand, smart digitalization of central government administration and national public services, besides these elements characteristic for local level of government organization, also includes an integrative approach and global impact on all economic and social activities in society. 32 An integrative approach includes general connection all digital public services with horizontal and vertical integration of services providing. Global impact to all economic and social activities defines the influence of smart digitalization on all aspects of public activity in the community.…”

Section: The Main Aspects Of Smart Digitalization In the Public Admin...mentioning

confidence: 99%

Smart Digitalization and Public Services in the Eu

Klarić

2023

EU and Comparative Law Issues and Challenges Series

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„Smart digitalization “is a term which describes the implementation of contemporary information technologies and application of digital solutions in improving various public services in society. The main aspect of smart digitalization is the promotion of smart digital services such as „smart cities “, „smart government “and „smart administration “, which represent digitalization of various local, regional and central government activities in the true creation of a common digital platform with a unique approach. A common and unique platform of public services can assure their provision and delivery to various users in society, and the possibility to choose the type of services which they need in daily life. Another aspect of „smart digitalization “is participation in political life of the community by using digital services as a main tool to canalize political processes in the community. An additional element of „smart digitalization “is the harmonization of digital public services, which can assure efficient and economic functioning of public institutions, central and local administrative bodies and different levels of government authority. That approach can be important in the context of green transformation of the EU, which represents one of the main EU public policies, connected with the transition of the European economy and society in the direction of sustainable development. This paper will analyze the main elements of the integrative approach in the implementation of digital technologies in public services. Elements of the integrative approach can be divided according to the implementation of digital technologies in central government digital services, regional government, digital services and local government digital services. The second division of smart digitalization can be divided into e-democracy and e-administration, where e-democracy represents the implementation of information technology in democratic processes in society, and e-administration includes implementation of information technologies in the functioning of administrative bodies and the delivery of public services and goods to the citizens, companies and other social, economic and political subjects in society. In this paper as a research methodology deductive and synthetic approach will be used to describe the main aspects of the implementation of a „smart digitalization “policy and analyze its influence on the sustainable transformation of European society. The applied methodology needs to explain how the implementation of “the smart digitalization “policy in public services impacts on green transition and the social transformation of European society in the direction of sustainable development and strengthening energy independency.

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The future regulation of artificial intelligence systems in healthcare services and medical research in the European Union

Cited by 39 publications

References 25 publications

CLASSICA: Validating artificial intelligence in classifying cancer in real time during surgery

CLASSICA: Validating artificial intelligence in classifying cancer in real time during surgery

Artificial intelligence in clinical pharmacology: A case study and scoping review of large language models and bioweapon potential

Smart Digitalization and Public Services in the Eu

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