On the issue of ethical aspects of the artificial intelligence systems implementation in healthcare

Sharova, Daria E.; Zinchenko, V.V.; Ахмад, Е. С.; Мокиенко, О. А.; Vladzymyrskyy, A.V.; Morozov, S. P.

doi:10.17816/dd77446

Cited by 8 publications

(4 citation statements)

References 9 publications

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“…The 73 included studies covered a broad spectrum of medical contexts, summarised with the main ethical issues raised and key findings in Supplementary Table S2. Briefly, the most frequently addressed areas were as follows: the general use of AI for healthcare (36 studies) , the use of AI in decision support systems (eight studies) [78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94], big data (four studies) [95][96][97][98], robotics (seven studies) [99][100][101][102][103][104][105] and adaptive AI (one study) [106]. The remaining studies addressed the following: rehabilitation [107], medical education [108], monitoring technology for the elderly [109], mental health [110], radiation technology [111], chatbots [112], health apps [113] and healthcare in low-and middleincome countries [114].…”

Section: Study Characteristicsmentioning

confidence: 99%

“…A total of 33 of the included papers examined the challenges and considerations surrounding the use of AI, particularly in healthcare, and the imperative of safeguarding confidentiality in the digital age [42][43][44]46,47,50,53,54,[58][59][60][61][66][67][68]71,72,[74][75][76]84,90,93,94,96,98,102,104,105,[109][110][111]113].…”

Section: Confidentialitymentioning

confidence: 99%

“…Trust was discussed as a theme in 34 of the included studies [42,50,52,54,[58][59][60][61][62][63][66][67][68]72,73,76,77,[79][80][81][82]86,87,89,90,93,94,101,102,105,107,110,112,113], with most focusing on clinical decision support systems, chatbots and robots. Most of these studies were articles or qualitative analyses.…”

Section: Trustmentioning

confidence: 99%

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Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices

Maccaro,

Stokes,

Statham

et al. 2024

JPM

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The use of AI in healthcare has sparked much debate among philosophers, ethicists, regulators and policymakers who raised concerns about the implications of such technologies. The presented scoping review captures the progression of the ethical and legal debate and the proposed ethical frameworks available concerning the use of AI-based medical technologies, capturing key themes across a wide range of medical contexts. The ethical dimensions are synthesised in order to produce a coherent ethical framework for AI-based medical technologies, highlighting how transparency, accountability, confidentiality, autonomy, trust and fairness are the top six recurrent ethical issues. The literature also highlighted how it is essential to increase ethical awareness through interdisciplinary research, such that researchers, AI developers and regulators have the necessary education/competence or networks and tools to ensure proper consideration of ethical matters in the conception and design of new AI technologies and their norms. Interdisciplinarity throughout research, regulation and implementation will help ensure AI-based medical devices are ethical, clinically effective and safe. Achieving these goals will facilitate successful translation of AI into healthcare systems, which currently is lagging behind other sectors, to ensure timely achievement of health benefits to patients and the public.

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Section: Study Characteristicsmentioning

confidence: 99%

Section: Confidentialitymentioning

confidence: 99%

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Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices

Maccaro,

Stokes,

Statham

et al. 2024

JPM

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“…The World Health Organisation (WHO) identified several ethical principles that should be followed during the process of SaMD-AI development and use [4,5]. Among others aspects, the WHO noted the rule for transparency, explainability of AI technologies.…”

Section: Introductionmentioning

confidence: 99%

Changes in software as a medical device based on artificial intelligence technologies

Zinchenko¹,

Chetverikov²,

Ахмад³

et al. 2022

Int J CARS

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Purpose to develop a procedure for registering changes, notifying users about changes made, unifying software as a medical device based on artificial intelligence technologies (SaMD-AI) changes, as well as requirements for testing and inspectionsquality control before and after making changes. Methods The main types of changes, divided into two groups-major and minor. Major changes imply a subsequent change of a SaMD-AI version to improve efficiency and safety, to change the functionality, and to ensure the processing of new data types. Minor changes imply those that SaMD-AI developers can make due to errors in the program code. Three types of SaMD-AI testings are proposed to use: functional testing, calibration testing or control, and technical testing. ResultsThe presented approaches for validation SaMD-AI changes were introduced. The unified requirements for the request for changes and forms of their submission made this procedure understandable for SaMD-AI developers, and also adjusted the workload for the Experiment experts who checked all the changes made to SaMD-AI. Conclusion This article discusses the need to control changes in the module of SaMD-AI, as innovative products influencing medical decision making. It justifies the need to control a module operation of SaMD-AI after making changes. To streamline and optimize the necessary and sufficient control procedures, a systematization of possible changes in SaMD-AI and testing methods was carried out. KeywordsArtificial intelligence • Medical software based on artificial intelligence technologies • Software as a medical device • Modifications • Changes • Validation B Ekaterina Akhmad

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Coronary artery calcification in the Moscow population (based on the Moscow Experiment on the use of computer vision in medical imaging)

Vasilev¹,

Vladzymyrskyy²,

Shulkin³

et al. 2023

Preprint

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Introduction: The challenges related to the prevention, diagnosis, and treatment of cardiovascular diseases remain acute. One of the measures to prevent these conditions from occurring is early detection of risk factors, one of which is coronary calcium. The latest achievements in computer vision made it possible to conduct opportunistic screening for coronary calcium. Objective: To study the prevalence of coronary artery calcification (CAC) as a risk factor for cardiovascular diseases in the Moscow population based on automated analysis of imaging findings. Materials and methods. A retrospective descriptive epidemiology study was carried out. Chest CT studies of 165,234 patients were analyzed. AI services carried out the automated analysis to detect CAC and to calculate the CAC score (CACS). Results. Coronary calcium was detected in 61.4% of the participants. The proportion of diagnosed men was 68.9% (of all men), women 55.7% (of all women) (р<0.001). The CAC score ranged between 1 to 60,306; the mean value was 558.2. The mean CACS increase for the entire population was 170.75; the mean growth was 168.13% the mean growth rate was 68.13%. 47.6% of men and 36.5% of women had clinically significant CACS (p<0.001). Most participants with clinically significant CAC belonged to Elderly and Senile age groups (42.0% each). Conclusions. The prevalence of coronary calcium in the Moscow population was 8.03 per 1000 people. CAC (including clinically significant) was significantly more common in men. The mean CACS was significantly higher compared to the female population across most age groups. There is a continuous increase in the mean CACS with age.

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On the issue of ethical aspects of the artificial intelligence systems implementation in healthcare

Cited by 8 publications

References 9 publications

Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices

Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices

Changes in software as a medical device based on artificial intelligence technologies

Coronary artery calcification in the Moscow population (based on the Moscow Experiment on the use of computer vision in medical imaging)

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