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Artificial intelligence in healthcare is the application of artificial intelligence (AI) to analyze and understand complex medical and healthcare data. In some cases, it can exceed or augment human capabilities by providing better or faster ways to diagnose, treat, or prevent disease.
The Russian health care system is based on the principles of the Soviet health care system, which was oriented on mass prophylaxis, prevention of infection and epidemic diseases, vaccination and immunization of the population on a socially protected basis. The current government health care system consists of several directions:
The need to extract usable public health information from the mass of data available requires the public health informaticist to become familiar with a range of analysis tools, ranging from business intelligence tools to produce routine or ad hoc reports, to sophisticated statistical analysis tools such as DAP/SAS and PSPP/SPSS, to Geographical ...
A clinical decision support system (CDSS) is a health information technology that provides clinicians, staff, patients, and other individuals with knowledge and person-specific information to help health and health care. CDSS encompasses a variety of tools to enhance decision-making in the clinical workflow.
Often, a clinical trial management system provides data to a business intelligence system, which acts as a digital dashboard for trial managers. [5] [6] [7] CTMSs allow experts easily to access centralized data and thus reducing the number of delayed trials. Sponsors can work with a database of previously researched contacts and names of ...
The scale and capabilities of artificial intelligence (AI) systems are growing rapidly, notably due to advances in big data. In healthcare, it is expected to provide easier accessibility of information, and to improve treatments while reducing cost. The integration of AI in healthcare tends to improve the quality and efficiency of complex tasks.
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