Logical, Philosophical and Ethical Aspects of AI in Medicine

Varlamov, O. O.; Chuvikov, D. A.; Adamova, L. E.; Petrov, Maxim; Zabolotskaya, Irina K.; Жилина, Т Н; Ltd, Moscow and Mivar

doi:10.18178/ijmlc.2019.9.6.885

Cited by 26 publications

(6 citation statements)

References 6 publications

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“…However, we need to emphasize that AI systems should be cognitive co-agents to assist human intelligence and not compete with it or even replace it (Jarrahi 2018 ). In line with the studies of (Horn 2001 ; Varlamov et al 2019 ), AI systems are essential tools to assist the healthcare professional find a comprehensive picture of the patient’s situation.…”

Section: Discussionmentioning

confidence: 88%

Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic

2021

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Section: Discussionmentioning

confidence: 88%

Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic

2021

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“…Ethical and Legal Considerations-Dealing with private medical information [15], such as patient records and genetic data, raises ethical and legal questions. To preserve patient privacy and uphold ethical standards, it is crucial to comply with data protection laws, provide informed consent, and adopt strong security measures.…”

Section: Issues and Challengesmentioning

confidence: 99%

Research Article Describing the Model for Predicting Breast Cancer

2023

IRJMETS

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Around the world, breast cancer is a major health problem, and patient outcomes are greatly improved by early identification. Machine learning approaches have become effective tools for predicting breast cancer in recent years. This abstract outlines a method for predicting breast cancer using machine learning algorithms. It starts with the acquisition of many, thoroughly annotated datasets that include clinical characteristics, genetic data, and imaging data. Preprocessing of the data is rigorous and includes feature selection, normalization, and cleaning. The created breast cancer prediction model shows excellent resilience and accuracy in identifying breast cancer patients. Modern explainable AI approaches are used to understand and visualize the model's predictions in order to get insights into the main variables affecting such predictions. The usage of a web-based platform for the breast cancer prediction model is explored, with special emphasis on the platform's userfriendly interface and interaction with clinical procedures. Users of the application may enter pertinent data to receive personalized risk assessments and recommendations for next steps. The study's conclusion highlights the potential of machine learning for breast cancer prediction. Additionally underlined are the possible advantages of real-time risk monitoring and the significance of ethical issues when using these models in clinical practice.

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“…In addition to these bene ts, the use of AI in anesthesia is accompanied by speci c ethical and social issues that require careful examination and deep understanding. numerous healthcare professionals express dissent regarding the integration of arti cial intelligence (AI) within the realm of anesthesiology, citing concerns related to ethical considerations, job displacement, and professional autonomy (10,11). There exists substantial apprehension within the healthcare community regarding the adoption of AI systems in the absence of thorough validation and transparency (12).…”

Section: Introductionmentioning

confidence: 99%

Ethical Implications of Artificial Intelligence in Anesthesiology: A Scoping Review

Sarkhosh,

Kiaei,

Aligholizadeh

et al. 2024

Preprint

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Background Nowadays Artificial Intelligence (AI) as one of the advanced and rapidly growing technologies has had widespread effects on various aspects of human life. In the healthcare sector, the adoption of AI methodologies has gained significant momentum, particularly in enhancing patient care, with anesthesiology emerging as a field keenly embracing these technological advancements. The use of AI in anesthesia is accompanied by specific ethical and social issues that require careful examination and deep understanding. The objective of this scoping review was to compile existing literature about the ethical considerations surrounding the utilization of artificial intelligence (AI) in anesthesiology. Method This scoping review was conducted within the first three months of 2024. The research question was "What are the ethical issues in the application of AI in anesthesia"? Based on the research question, researchers initially extracted relevant keywords using Medical Subject Heading (MeSH) and independently conducted preliminary searches in databases including Scopus, Web of Science, PubMed, Cochrane, and Google Scholar. The study selection process was guided by predetermined inclusion and exclusion criteria. The inclusion criteria were studies relevant to the research question. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was used to report the review process. Results The search strategy yielded a total of 327 articles. Consequently, the full text of 4 studies was examined. Of these, 2 studies were excluded due to lack of relevance to the research question. In total, 2 studies (both in English) were included in this review. Both of these studies were cross-sectional studies that examined the opinions of anesthesiologists regarding the ethical implications of using artificial intelligence in anesthesia. Conclusion The ethical integration of AI into anesthesia holds promise for improving patient care outcomes while upholding principles of safety, fairness, and accountability. Additional training programs and updated protocols are necessary for ensuring data security, collection, and processing. Additionally, Appropriate legal regulations concerning data processing should be developed.

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Logical, Philosophical and Ethical Aspects of AI in Medicine

Cited by 26 publications

References 6 publications

Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic

Reflections on epistemological aspects of artificial intelligence during the COVID-19 pandemic

Research Article Describing the Model for Predicting Breast Cancer

Ethical Implications of Artificial Intelligence in Anesthesiology: A Scoping Review

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