MODERN APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN CLINICAL DIAGNOSTICS
Abstrak
This article discusses the modern applications of artificial intelligence in clinical diagnostics. Artificial intelligence technologies such as Machine Learning and Deep Learning are widely used in disease detection and medical image analysis. The study examines the advantages of AI, including high diagnostic accuracy, rapid data processing, and reduction of human errors. The role of intelligent systems in radiology, cardiology, and oncology is also analyzed. In addition, the article highlights challenges related to data security, ethical issues, and technical limitations. International experiences in the implementation of AI in healthcare are reviewed. The research concludes that artificial intelligence is becoming an important component of modern clinical diagnostics.
Iqtiboslar
Turing, A. M. (1950). Computing Machinery and Intelligence. Mind Journal.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature.
Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine learning in medicine. New England Journal of Medicine.
Litjens, G. et al. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis.
Esteva, A. et al. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature.
World Health Organization (WHO). (2021). Ethics and governance of artificial intelligence for health.
Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
IBM Watson Health. Official publications and reports.
Google Health AI. Research reports and technical documentation.
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