The Future of Medicine and the Logic of Data Management - Data Discrimination Problems

Abstract

Considered problems of medical data management. It is emphasized that this process has the greatest potential to ensure accurate and cost-effective patient care, as well as knowledge transfer during medical education. Analyzing the main areas of professional application of data: integration of big data, working with data of various types (from batch to stream) and their transformation for further use, we note that all the listed areas do not have a clear interpretation and recommendations for their use. The purpose of the study was to substantiate the strategy of a safe and effective medical data management system and the logic of creating completely open data systems. This strategy will allow streamlining the data flows of instrumental and laboratory studies and ensure the delivery of their big data directly to medical institutions or medical research centers. Conclusions: 1. There is a need for a comprehensive real-time medical data management system that will allow physicians, patients, and external users to enter their medical and lifestyle data into the system. 2. The inclusion of big data analytics will help to better predict or diagnose diseases, and accordingly help in the development of an effective plan for the prevention of complications and treatment of the disease. 3. Scaling communication with each patient in real time is possible only with the help of artificial intelligence. Manual intervention simply cannot serve thousands of users at the same time, each in their own way, addressing each individual directly. This conclusion should be especially emphasized when creating a perfect model of family medicine organization. 4. Transferring information is at the heart of developmental biology, and thus it is imperative that we can form a logical and structured approach to the healthcare language. If, as it appears, information theory has much offer to biology, further advances will depend on its integration. Given that these fields share many terms with developmental biology, effective collaboration may necessitate redefining the meaning attached to signaling, communication and information, in the context of the biology and medicine. Biosemiotics is inherently concerned with the language and rules of signals and codes in biological systems. It combines many ideas from diverse areas including systems theory, information theory and linguistics and may offer us a new perspective on the classification and meaning of biological and medical signaling.