Nanorevolution in medicine: synergy of nanotechnology, artificial intelligence and digital innovation

Seliverstov, D.

doi:10.29296/25879979-2024-07-06

Medsestra

2024

DOI: 10.29296/25879979-2024-07-06

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Nanorevolution in medicine: synergy of nanotechnology, artificial intelligence and digital innovation

D. Seliverstov

Abstract: This article analyses the potential of integrating nanotechnology, artificial intelligence and digital innovations in medicine. Promising applications of these technologies are discussed, including personalised nanomedicine, the fight against antibiotic resistance and the development of neuronanointerfaces. Particular attention is paid to the role of artificial intelligence in analysing data from nanosensors, designing nanostructures and controlling nanorobots. Ethical and legal aspects of the application of n… Show more

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2024

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Cited by 3 publications

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Using Artificial Intelligence for Biomarker Analysis in Clinical Diagnostics

Seliverstov,

Kutsenko,

Gorelova

et al. 2024

Mol Med Rus

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Introduction. Artificial intelligence (AI) technologies are becoming crucial in clinical diagnostics due to their ability to process and interpret large volumes of data. The implementation of AI for biomarker analysis opens new opportunities in personalized medicine, offering more accurate and individualized approaches to disease diagnosis and treatment. The relevance of this review stems from the need to systematize recent advances in AI application for biomarker analysis, which is critical for early diagnosis and prediction of chronic non-communicable diseases (NCDs). Material and methods. The analysis of peer-reviewed scientific publications and reports from leading research centers over the past five years was conducted. Studies on the application of AI algorithms for analyzing genomic, proteomic, and metabolomic biomarkers were reviewed, including machine learning methods and deep neural networks. Special attention was paid to the integration of multi-marker panels for improving the accuracy of diagnosis and prediction of cardiovascular, digestive, respiratory, endocrine system diseases, as well as oncological and neurodegenerative pathologies. Results. The application of AI has significantly increased the sensitivity and specificity of diagnostics, especially in complex cases requiring analysis of multiple disease parameters. The effectiveness of AI has been demonstrated in early diagnosis of lung, breast, and colorectal cancer, prediction of cardiovascular complications and NCDs progression, including diabetes mellitus and Alzheimer’s disease. AI’s significant contribution to the discovery of new biomarkers, optimization of personalized treatment, and improvement of therapeutic strategies has been noted. Conclusion. The use of AI in biomarker analysis has become a significant breakthrough in medical diagnostics, particularly in oncology, cardiology, and neurodegenerative diseases. The technology allows integration of data about various biomarkers and contributes to creating more accurate models for disease diagnosis and prediction. Further development is associated with technology advancement and overcoming ethical and regulatory barriers, which will expand AI capabilities in clinical practice.

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Using Artificial Intelligence for Biomarker Analysis in Clinical Diagnostics

Seliverstov,

Kutsenko,

Gorelova

et al. 2024

Mol Med Rus

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Artificial Intelligence in Nursing Practice: Legal Aspects and Transformation of the Profe ssional Role of Nurses

Seliverstov

2024

Medsestra

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The article examines the current issue of implementing artificial intelligence (AI) technologies in modern medical practice with a special focus on the role of nursing staff. The key areas of AI application in healthcare, the existing regulatory framework in the Russian Federation, and ethical aspects of using intelligent systems in medicine are analyzed. Particular attention is paid to the transformation of nurses’ professional competencies in the context of healthcare digitalization. Based on the analysis of current practices and technology development prospects, recommendations are proposed for adapting educational programs and professional standards for nursing staff.

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Ethical Norms for the Application of Artificial Intelligence in Medicine and the Role of Nurses

Kutsenko,

Nurmyradov,

Akhmedov

2024

Medsestra

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The integration of artificial intelligence (AI) into medical practice creates new opportunities to enhance the quality of healthcare while simultaneously posing significant ethical challenges. This article explores key ethical aspects of AI use in various fields of medicine, including genetic editing, molecular diagnostics, telemedicine, and clinical decision support systems. Special attention is given to the role of nurses in ensuring the ethical application of AI technologies and protecting patient rights. Current issues related to data confidentiality, informed consent, and potential risks of algorithmic bias are analyzed. The article emphasizes the need for a multidisciplinary approach to AI implementation and outlines the crucial role of nurses in this process.

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Nanorevolution in medicine: synergy of nanotechnology, artificial intelligence and digital innovation

Cited by 3 publications

References 11 publications

Using Artificial Intelligence for Biomarker Analysis in Clinical Diagnostics

Using Artificial Intelligence for Biomarker Analysis in Clinical Diagnostics

Artificial Intelligence in Nursing Practice: Legal Aspects and Transformation of the Profe ssional Role of Nurses

Ethical Norms for the Application of Artificial Intelligence in Medicine and the Role of Nurses

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