V. A. Kazakova, S. A. Tyulyakova, E. Shivilov, K. A. Anichkina, A. L. Miftakhova, D. D. Yurkanova
{"title":"Legal Basis for the Use of Artificial Intelligence Technologies in Radiation Diagnostics","authors":"V. A. Kazakova, S. A. Tyulyakova, E. Shivilov, K. A. Anichkina, A. L. Miftakhova, D. D. Yurkanova","doi":"10.52560/2713-0118-2023-2-63-77","DOIUrl":null,"url":null,"abstract":"The article considers the legal basis for the regulation of artificial intelligence (AI) technologies in domestic health care. Radiation diagnostics is one of the first areas of medicine where AI is being introduced to analyze radiographs and form draft conclusions for the examination. Due to the opaqueness of the decisionmaking process («black box effect») and high error rate, the level of trust of specialists and patients in innovations remains low. In this connection, there is an objective need to create effective legal mechanisms that provide for measures of responsibility for erroneous AI decisions, protecting the rights of doctors and patients in the operation of these programs.","PeriodicalId":51864,"journal":{"name":"Radiology Research and Practice","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiology Research and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52560/2713-0118-2023-2-63-77","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
The article considers the legal basis for the regulation of artificial intelligence (AI) technologies in domestic health care. Radiation diagnostics is one of the first areas of medicine where AI is being introduced to analyze radiographs and form draft conclusions for the examination. Due to the opaqueness of the decisionmaking process («black box effect») and high error rate, the level of trust of specialists and patients in innovations remains low. In this connection, there is an objective need to create effective legal mechanisms that provide for measures of responsibility for erroneous AI decisions, protecting the rights of doctors and patients in the operation of these programs.
期刊介绍：
Radiology Research and Practice is a peer-reviewed, Open Access journal that publishes articles on all areas of medical imaging. The journal promotes evidence-based radiology practice though the publication of original research, reviews, and clinical studies for a multidisciplinary audience. Radiology Research and Practice is archived in Portico, which provides permanent archiving for electronic scholarly journals, as well as via the LOCKSS initiative. It operates a fully open access publishing model which allows open global access to its published content. This model is supported through Article Processing Charges. For more information on Article Processing charges in gen
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