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The purpose of the research is to to develop an intelligent decision support system for physicians based on automated analysis of dermatoscopic images using machine learning algorithms, designed for early diagnostics and detection of malignant skin neoplasms. The development of an intelligent system for supporting physicians' decision making for both specialized specialists and general practitioners and nursing staff performing primary examination of patients with skin neoplasms is a research relevant area. Methods . The intelligent system architecture for supporting doctors' decision-making based on the analysis of dermatoscopic images is proposed. The configuration used is a network approach based on the client-server mode. The client is a web application implementing the doctor's personal account functionality. This server hosts a cloud infrastructure that collects, stores and analyzes dermatoscopic images, and also maintains a report on the nosological group of skin lesions. In the analyzing process dermatoscopic images, machine learning methods are used based on the neural network’s usage with the virtual transformer architecture and a formed set of dermatoscopic images. Results . The developed intelligent system for supporting physician decision-making has been practically implemented and tested in clinical conditions. It is characterized by accuracy values exceeding 93% for the Accuracy indicator and 89% – F-measure at the training stage and more than 89% (Accuracy indicator) during medical examinations. The obtained values of experimental assessments made it possible to formulate recommendations for integrating the developed intelligent system for supporting physician decision-making into the work processes of medical institutions. Conclusion. The developed system provides automated image analysis, metadata structuring, visualization of model predictions and the possibility of expert marking and can be used not only by specialized doctors during medical examinations and studies, but also by general practitioners and mid-level medical personnel during screening examinations, mobile preventive appointments and medical examinations.
Published in: Proceedings of the Southwest State University Series IT Management Computer Science Computer Engineering Medical Equipment Engineering
Volume 15, Issue 3, pp. 50-65