Abstract
The problems of using artificial intelligence in health care were discussed. The aim of the study. Assess the possibilities of using artificial intelligence in medicine right now. Most studies comparing the performance of AI and clinicians are not valid because the tests are not large enough or come from different sources. This difficulty could be overcome in the era of an open healthcare system. Indeed, open data and open methods are sure to attract a lot of attention as new research methods. It also highlights the idea that AI technologies can improve accuracy by incorporating additional data for self-updating, but automatically incorporating low-quality data can lead to inconsistent or inferior algorithm performance. The conclusion made is that the introduction of artificial intelligence into clinical practice is a promising field of development that is rapidly developing along with other modern fields of precision medicine. One of the fundamental issues remains the solution of ethical and financial issues related to the introduction of artificial intelligence
Publisher
National Academy of Sciences of Ukraine (Co. LTD Ukrinformnauka) (Publications)
Reference16 articles.
1. Newmarker C. Digital Surgery tout's artificial intelligence for the operating room. Medical Design and Outsourcing. Medical Design and Outsourcing; 2018. DOI:https://www.medicaldesignandoutsourcing.com/digital-surgery-touts-artificial-intelligence-for-the-operating-room/.
2. Wijnberge M., Geerts B. F., Hol L., Lemmers N., Mulder M. P., Berge P., et al. Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. JAMA 2020;323:l052-60.
3. Khalsa R. K, Khashkhusha A., Zaidi S., Harky A., Bashir M. Artificial intelligence and cardiac surgery during the COVID-19 era. J Card Surg. 2021 May;36(5):1729-1733.
4. Dias R. D., Shah J. A, Zenati M. A. Artificial intelligence in cardiothoracic surgery. Minerva Cardioangiol. 2020 Oct;68(5):532-538. DOI: 10.23736/S0026-4725.20.05235-4.
5. Kilic A. Artificial Intelligence and Machine Learning in Cardiovascular Health Care. Ann Thorac Surg. 2020 May;109(5):1323-1329.