EARLY-STAGE DISEASE DETECTION SYSTEM BASED ON AI – MISU

Abstract

Research Objective. The development and justification of approaches for implementing digital health monitoring tools based on the MISU case – with an emphasis on the use of AI, integration of data from wearable devices, analysis of family health history (FHH), and the creation of a unified ecosystem for prevention, prediction, and response to changes in population health. Materials and Methods. To achieve the stated objective, general scientific and mathematical research methods were used. The research materials included domestic and international IT solutions, AI technologies, and mathematical models. The article also incorporates materials from the Qualification Project. Results. An analysis of primary healthcare challenges, AI capabilities, existing global solutions, and AI functionalities revealed commonalities and differences in their potential for combined use across various countries, fields, and solutions. Joint application models already exist within Ukrainian digital healthcare solutions, and here is a description of how they can function: • CheckEye – AI for Early Detection of Ophthalmic Complications CheckEye is a Ukrainian AI platform for diagnosing diabetic retinopathy through retinal image analysis. The system can detect pathologies at early stages with over 90% accuracy, helping to prevent vision loss in diabetic patients. • Integration potential with MISU: The MISU platform can utilize the CheckEye API for automatic referral of patients in risk groups for further ophthalmologic examination or rehabilitation support. • Mark – AI for Medical Image Analysis Mark is a Ukrainian startup creating services for analyzing X-rays, CT scans, and MRI images. The platform uses deep learning to automatically detect pathologies such as pneumonia, tuberculosis, and oncological processes. • Integration potential with MISU: Adding Mark to MISU would allow for instant analysis of images from field conditions, particularly within military medicine, rehabilitation, or mobile diagnostic units. Conclusions: The implementation of the MISU platform in Ukrainian medical institutions demonstrates a strong potential for transforming the healthcare system. Thanks to its ability to automate numerous processes – including stress detection, health monitoring of military personnel, patient rehabilitation support, disease prediction, and workload reduction for physicians – MISU can become a vital tool for ensuring efficient and timely healthcare delivery.