Russian Student Develops Medical Neural Network for More Accurate Diagnoses
The AI system relies exclusively on verified medical data when analyzing patient tests.
Sofya Onishchenko, a fourth-year student at the Faculty of Applied Mathematics and Cybernetics at Tver State University, has developed a medical neural network capable of analyzing X-rays, CT scans, cardiograms, and other screening results. The system is designed to help physicians make accurate diagnoses based on validated medical knowledge.
Onishchenko added that the platform is now being integrated with the databases of several medical institutions in the Tver region. A pilot phase is set to begin soon.
Other Digital Assistants
Medical institutions in the Moscow region are already actively testing an AI diagnostician called AIDA. The digital assistant aims to improve diagnostic accuracy and reduce the risk of errors. The system analyzes a patient’s medical record and suggests one of 95 of the most common diagnoses.
Another widely used medical development is the clinical decision support system Doktor Pirogov (Doctor Pirogov). It was created by researchers at the Artificial Intelligence Research Center of Novosibirsk State University. The physician’s digital assistant includes information on 250 major diseases. The list is expected to expand with additional data in the future.
