TY - CONF
T1 - Artificial intelligence and machine learning technologies as innovative medical devices
AU - Žukovs, Artūrs
N1 - Conference code: 2
PY - 2021/3/24
Y1 - 2021/3/24
N2 - The focus of this article will be the research of Latvian regulatory enactments in the context of medical devices, identifying whether artificial intelligence technologies fit between them. The research aim is to indicate the meaning and depth of the term medical device, and determining whether artificial intelligence, which is taught by machine learning technology, is identifiable as a medical device. At the same time, it will be concluded whether the existing regulatory framework also includes the regulation of artificial intelligence technologies in the field of health care or nevertheless leaves it unregulated. In order to achieve the set objective, Latvian regulatory enactments will be analyzed, for example, European Parliament and Council Regulation No. 2017/746 on in vitro diagnostic medical devices, European Parliament and Council Regulation No. 2017/745, Medical Treatment Law, Cabinet Regulation No. 468 on approval of medical technologies used in treatment and introduction of new medical technologies procedures, Cabinet of Ministers Regulations No. 689 on the Procedure for Registration, Conformity Assessment, Distribution, Operation and Technical Supervision of Medical Devices and other regulatory enactments. An analytical and descriptive method will be used for the research. The analytical method will help to analyse the medical device term and on what principles it is determined, meanwhile, descriptive method will describe the artificial intelligence and machine learning technology definition and processes. As a result, it will be clarified that artificial intelligence technologies used in healthcare and using machine learning technology meet the national definition of a medical device, regardless of the complexity of the program algorithm or the amount of training received. Given that artificial intelligence trained in machine learning technology qualifies as a medical device, it is subject to the same criteria governing a medical device, according to the respective risk of the medical device affecting the patient.
AB - The focus of this article will be the research of Latvian regulatory enactments in the context of medical devices, identifying whether artificial intelligence technologies fit between them. The research aim is to indicate the meaning and depth of the term medical device, and determining whether artificial intelligence, which is taught by machine learning technology, is identifiable as a medical device. At the same time, it will be concluded whether the existing regulatory framework also includes the regulation of artificial intelligence technologies in the field of health care or nevertheless leaves it unregulated. In order to achieve the set objective, Latvian regulatory enactments will be analyzed, for example, European Parliament and Council Regulation No. 2017/746 on in vitro diagnostic medical devices, European Parliament and Council Regulation No. 2017/745, Medical Treatment Law, Cabinet Regulation No. 468 on approval of medical technologies used in treatment and introduction of new medical technologies procedures, Cabinet of Ministers Regulations No. 689 on the Procedure for Registration, Conformity Assessment, Distribution, Operation and Technical Supervision of Medical Devices and other regulatory enactments. An analytical and descriptive method will be used for the research. The analytical method will help to analyse the medical device term and on what principles it is determined, meanwhile, descriptive method will describe the artificial intelligence and machine learning technology definition and processes. As a result, it will be clarified that artificial intelligence technologies used in healthcare and using machine learning technology meet the national definition of a medical device, regardless of the complexity of the program algorithm or the amount of training received. Given that artificial intelligence trained in machine learning technology qualifies as a medical device, it is subject to the same criteria governing a medical device, according to the respective risk of the medical device affecting the patient.
M3 - Abstract
SP - 45
T2 - RSU Research week 2021: PLACES
Y2 - 25 March 2021 through 25 March 2021
ER -