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ВИКОРИСТАННЯ МЕТОДУ МОНТЕ-КАРЛО ДЛЯ МАРКОВСЬКИХ ЛАНЦЮГІВ ДЛЯ ПРОГНОЗУВАННЯ ПОШИРЕНОСТІ ІШЕМІЧНОЇ ХВОРОБИ СЕРЦЯ В УКРАЇНІ
2018
Medična Informatika ta Inženerìâ
In medical forecasting, there are often challenges in which it is necessary to assess the risk that is continuous for a long time, and important events can occur more than once. One of the ways of solving problems of this type is the use of Markov models.Markov models suggest that the patient is always in one of the finite numbers of discrete states of health, called the Markov states. All events are modeled as a transition from one state to another. In order for the Markov chain to end, it
doi:10.11603/mie.1996-1960.2017.4.8466
fatcat:jv5e2ld5xnafzfp4qzdvfvaa5m