Искусственный интеллект в здравоохранении России: сбор и подготовка данных для машинного обучения.

Abstract

This scientific article draws attention to the importance of collecting and preparing high-quality medical data for the development of artificial intelligence (AI) systems in Russian healthcare. Materials and methods. The main emphasis is on the need to create a unified federal standard for collecting structured digitized medical data, which will unify the processes of collecting and generating datasets for medical organizations. Results. The article proposes the introduction of digital assistants, including pre-medical diagnostic questionnaires, mobile applications and software modules for medical examinations, which will reduce the time spent filling out medical documentation and ensure the collection of more complete and accurate information. The next step is to reengineer the health data collection process, including patient engagement via smartphones and personal health assistants. The article identifies methodological problems such as unreliability, incompleteness and lack of extensional knowledge in the collected data, and proposes a roadmap for the development of a health data collection system, including the creation of digital standards, data collection methods and the development of AI-based decision support. Conclusions. Solving the described problems and the data development plan are important for the successful implementation of the national project «Data Economy», supporting the development and application of AI systems in the medical field.