Alena Gennadievna Deryaeva1, Vladimir Petrovich Kosolapov2, Olga Gennadievna Deryaeva3, Galina Vladimirovna Sych4, Alexander Yurievich Goncharov5, Roman Evgenievich Tokmachev
Pakistan Journal of Medical & Health Sciences




Peer Reviewed

Previous Published Issues


Prediction of Reproductive Disorders in Women in Industrial Enterprises Using Digital Technologies

Alena Gennadievna Deryaeva1, Vladimir Petrovich Kosolapov2, Olga Gennadievna Deryaeva3, Galina Vladimirovna Sych4, Alexander Yurievich Goncharov5, Roman Evgenievich Tokmachev



1811



Abstract

Background: The organization of medical care for workers and employees remains an important form in industrial medicine.

Aim: Creation of software for workers of an industrial enterprise, using the developed models, which will reveal the risk factors for the occurrence of diseases of the reproductive system in women of fertile age and optimize the work of doctors at outpatient appointments with the aim of early prevention of diseases and further observation of the patient.

Methods: To develop the program, 2 groups of 469 women of reproductive age were formed. Using the database, prognostic models were built to identify the likelihood of the development of reproductive system disorders in women, which made it possible to create an algorithm, and later software in order to select optimal medical and social measures.

Results: We have created a computer program to simplify the application of the algorithm in practice.

Conclusion: The developed complex algorithm with an assessment of the informational significance of the parameters will make it possible to predict with high accuracy the development of diseases of the reproductive system in patients of reproductive age. This approach will make it possible to determine the tactics of optimal medical and social measures for managing patients with pathology or the possibility of developing diseases of the reproductive system, to preserve their reproductive health.

MeSH words: Occupational medicine, software, reproductive health, predictive models, prevention.



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