Medical education, postgraduate, Artificial Intelligence


The field of postgraduate medical education is continuously evolving, with advancements in technology playing a significant role in shaping its future. One such advancement is the integration of artificial intelligence (AI) or piece intelligence (PI) into


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Beam AL, Drazen JM, Kohane IS, Leong TY, Manrai AK, Rubin EJ. Artificial Intelligence in Medicine. N Engl J Med. 2023 Mar 30;388(13):1220-1221. doi: 10.1056/NEJMe2206291.

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115-118.

Chen, T., Li, Y., Li, M., Wei, D., Shi, Y., Zhang, L., ... & Sun, J. (2019). A prediction model for cardiovascular disease risk prediction using random forest. BMC Medical Informatics and Decision Making, 19(1), 1-10.

Stokes, J. M., Yang, K., Swanson, K., Jin, W., Cubillos-Ruiz, A., Donghia, N. M., ... & Collins, J. J. (2020). A deep learning approach to antibiotic discovery. Cell, 180(4), 688-702.

Liao, K. P., Cai, T., Savova, G. K., Murphy, S. N., Karlson, E. W., & Ananthakrishnan, A. N. (2015). Development of phenotype algorithms using electronic medical records and incorporating natural language processing. BMJ, 350, h1885.

Rogers, C. G., & Laungani, R. G. (2018). Applications of robotics in endourology. Asian Journal of Urology, 5(2), 83-90.

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., ... & Sánchez, C. I. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42, 60-88.Artificial Intelligence is increasingly integrated into postgraduate medical education, supporting personalized learning experiences and augmenting diagnostic accuracy. AI-powered systems can analyze vast amounts of medical data, assist in differential diagnoses, and recommend treatment plans based on evidence-based guidelines. Additionally, AI-driven adaptive learning platforms can tailor educational content to individual learners, catering to their strengths and weaknesses.

Hsu C, Sandford B. The Delphi Technique: Making Sense of Consensus. Practical Assessment, Research & Evaluation. 2007;12(10):1-8.

Cook DA, Triola MM. Virtual Patients: A Critical Literature Review and Proposed Next Steps. Medical Education. 2009;43(4):303-311.

Tolsgaard MG, et al. Feedback on Virtual Patients: An Iterative Approach to the Development of a Systematic Review Protocol. JMIR Research Protocols. 2013;2(2):e29.

Braun D, et al. Artificial Intelligence in Medical Education: A Review. In: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). 2018. IEEE.

Wendel Garcia PD, et al. Artificial Intelligence as a Virtual Mentor in Medicine. Cureus. 2021;13(1):e12622.

Topol EJ. High-performance Medicine: The Convergence of Human and Artificial Intelligence. Nature Medicine. 2019;25(1):44-56.

Norgeot B, et al. Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis. JAMA Network Open. 2019;2(3):e190606.



How to Cite

Пашковський, В., Пашковська, Н., & Царик, І. (2023). PERSPECTIVES OF USING ARTIFICIAL INTELLIGENCE IN POSTGRADUATE MEDICAL EDUCATION. SWorldJournal, 2(20-02), 61–64.




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