Development, evaluation and validation of machine learning models to predict hospitalizations of patients with coronary artery disease within the next 12 months.

Journal: International journal of medical informatics
Published Date:

Abstract

BACKGROUND: Improved survival of patients after acute coronary syndromes, population growth, and overall life expectancy rise have led to a significant increase in the proportion of patients with stable coronary artery disease (CAD), creating a significant load on the entire healthcare system. The disease often progresses with the development of many complications while significantly increasing the likelihood of hospitalization. Developing and applying a machine learning model for predicting hospitalizations of patients with CAD to an inpatient medical facility will allow for close monitoring of high-risk patients, early preventive interventions, and optimized medical care.

Authors

  • Andrey D Ermak
    K-SkAI LLC, Petrozavodsk, Russia.
  • Denis V Gavrilov
    K-SkAI LLC, Petrozavodsk, Russia.
  • Roman E Novitskiy
    K-SkAI LLC, Petrozavodsk, Russia.
  • Alexander V Gusev
    Federal Research Institute for Health Organization and Informatics, Moscow, Russia; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow, Russia.
  • Anna E Andreychenko
    K-SkAI LLC, Petrozavodsk, Russia; ITMO University, St. Petersburg, Russia. Electronic address: aandreychenko@webiomed.ru.