I.P. Korneeva1

1 St. Petersburg State Electrotechnical University "LETI" (St. Petersburg, Russia)
1 ipkorneeva@etu.ru

Standard clinical protocols for pregnancy management are focused on discrete observation and the physiological course of the process. If a patient has chronic non-communicable diseases or a pregnant woman is classified as a high-risk miscarriage group, this approach often leads to late detection of complications and a decrease in the effectiveness of preventive measures, which requires the introduction of more flexible methods for assessing the condition.

The purpose of the study is development of an extended pregnancy management protocol using intelligent monitoring methods that provides a personalized approach to monitoring pregnant women, taking into account their individual characteristics and the impact of chronic non-communicable diseases if they have a history.

The algorithm of the extended protocol has been developed, which includes the stages of initial assessment with the formation of an individual risk profile, dynamic monitoring using wearable devices and remote data transmission, as well as intelligent assessment of the condition and prediction of complications based on machine learning methods and time series analysis.

The proposed approach makes it possible to dynamically adjust the tactics of pregnancy management and the frequency of monitoring depending on the current condition of the patient. The results can be used in the creation of medical information and measurement systems, telemedicine platforms and support systems for medical decision-making in obstetrics.

Korneeva I.P. Development of an extended pregnancy management protocol using intelligent monitoring methods. Biomedicine Radioengineering. 2026. V. 29. № 3. P. 115–118. DOI: https:// doi.org/10.18127/ j15604136-202603-20 (In Russian)

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