National Support For Use Of Artificial Intelligence Technologies In Providing Medical Assistance For Oncological Diseases: The US Experience
Abstract
The article is focused on the role and capacity of an AI in combating cancer. It describes achievements and programs of the US National Institute of Cancer in the sphere of machine learning. The article offers the analysis of positive experience of the US National Institute of Cancer in regulatory, organizational and technological cooperation with the United States Department of Health and Human Services and the US Department of Energy in the area of formation and analysis of special registers’medical data with the purpose of effective diagnostics and proper treatment of oncological diseases and development of efficient medicinal drugs. The article presents prospects of national support to the development of new algorithms of AI models in the area of medical assistance to oncological patients. The author describes achievements and challenges to utilization of AI technologies in the US health care system, as well as ethical and legal issues which emerge in this process. It has been proven that absence of a universal Code of regulatory and legal acts of the USA and EU which would regulate algorithms, methods, and machine learning of big data processing in the area of health care leads to the absence of regulated procedures of attributing responsibility in case of harm caused by AI technologies to patients. The author recommends US and EU regulatory authorities to cooperate more actively with international medical research and development institutions (communities) with the aim of drafting relevant legislation and standards. The emphasis is made on a need to provide information protection of rights and freedoms of patients by way of making impossible any capturing of personal medical data irrespective of the form in which it is kept. The conclusion is made that implementation of AI technologies into medical practices is an important factor of government interference aimed at proper management of interaction processes between machines and humans as well as delegation of responsibilities for clinical decisions and potential mistakes.
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