Application of Hidden Markov Model to Identify Disease Progression Process in Medical Research

MADADIZADEH, Farzan and Yarahmadi, Mohammad and ZERAATI, Hojjat (2019) Application of Hidden Markov Model to Identify Disease Progression Process in Medical Research. Iran J Public Health.

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Abstract

Disease progression process means a change of disease stages during the times (1). Identifying how is progress the disease and the number of its stages can be very helpful to increase correct recognition and appropriate prescribing of medications in different disease treatments. Markov models are a ubiquitous and unique statistical model which can modeling different stages of diseases during time and identify the disease progression process (Fig. 1). The basic assumption of these models is a Markov property, it means that the current stage of the disease must be depend like a chain only on the previous time stage not on other stages that occurred earlier times

Item Type: Article
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine, Health and Life Sciences > School of Medicine
Depositing User: samira sepahvandy
Date Deposited: 21 Sep 2020 04:16
Last Modified: 21 Sep 2020 04:16
URI: http://eprints.lums.ac.ir/id/eprint/2337

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