Abstract
The use of artificial intelligence (AI) in the sphere of medicine is aimed at primary diagnostics of human body and finding treatment approaches and solutions. While some scientists consider that AI is able to detect many complicated diseases at early stages thus saving lives of many patients, human reasoning methods in the field of medicine cannot be fully replaced by machines. This paper aims to find out the optimal balance between human and AI participation in diagnostic and treatment decision processes. With this purpose a simulation of diseases based on 100 real-case anonymous data was generated to be diagnosed through independent and simultaneous AI and human analysis. As a result, the quantitative and qualitative outcomes were summarized and used to suggest a solution to combine AI and human participation, aimed at elimination disadvantages and most effective use of advantages of both sides.
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Murthy, S.K.: Automatic construction of decision trees from data: a multi-disciplinary survey. Siemens Corporate Research, Princeton, USA (n.d.). https://cs.nyu.edu/~roweis/csc2515-2006/readings/murthy_dt.pdf
Quinlan, J.R.: Industry of Decision Trees. Kluwer Academic Publishers (1985). https://link.springer.com/content/pdf/10.1007/BF00116251.pdf
Henriksen, K., Brady, J.: The pursuit of better diagnostic performance: a human factors perspective. BMJ Qual. Saf. (2013). https://qualitysafety.bmj.com/content/qhc/22/Suppl_2/ii1.full.pdf
Karimi, K., Hamilton, H.J.: Generation and interpretation of temporal decision rules. Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada (n.d.). https://arxiv.org/pdf/1004.3334.pdf
Quinlan, J.R.: Semi-autonomous acquisition of pattern-based knowledge. Baser Department of Computer Science, University of Sydney (n.d.). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.472.7028&rep=rep1&type=pdf
Albu, A.: From logical inference to decision trees in medical diagnosis. In: E-Health and Bioengineering Conference (EHB), pp. 65–68 (2017)
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Hambardzumyan, L., Ter-Sargisova, V., Baghramyan, A. (2020). The Role of Artificial Intelligence in Contemporary Medicine. In: Ahram, T., Karwowski, W., Vergnano, A., Leali, F., Taiar, R. (eds) Intelligent Human Systems Integration 2020. IHSI 2020. Advances in Intelligent Systems and Computing, vol 1131. Springer, Cham. https://doi.org/10.1007/978-3-030-39512-4_27
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DOI: https://doi.org/10.1007/978-3-030-39512-4_27
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