Analysis of Temporal Clinical Patterns using Hidden Markov Models
نویسندگان
چکیده
Analysis of complex clinical data in Electronic Health Record (EHR) using machine learning methods may help us to better understand the dynamics of the disease and importance of various patient management interventions. In this work, we study the problem of modeling the dynamics of postsurgical cardiac patient population. Our approach relies on the hidden Markov model to model temporal dynamics, and spectral clustering methods to approximate the number of hidden states of the models. We test the methodology by applying it to analyze medication order sequences extracted from EHRs of 2,878 post surgical cardiac patients.
منابع مشابه
مدل سازی فضایی-زمانی وقوع و مقدار بارش زمستانه در گستره ایران با استفاده از مدل مارکف پنهان
Multi site modeling of rainfall is one of the most important issues in environmental sciences especially in watershed management. For this purpose, different statistical models have been developed which involve spatial approaches in simulation and modeling of daily rainfall values. The hidden Markov is one of the multi-site daily rainfall models which in addition to simulation of daily rainfall...
متن کاملIntroducing Busy Customer Portfolio Using Hidden Markov Model
Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...
متن کاملIntrusion Detection Using Evolutionary Hidden Markov Model
Intrusion detection systems are responsible for diagnosing and detecting any unauthorized use of the system, exploitation or destruction, which is able to prevent cyber-attacks using the network package analysis. one of the major challenges in the use of these tools is lack of educational patterns of attacks on the part of the engine analysis; engine failure that caused the complete training, ...
متن کاملTemporal Data Mining Using Hidden Markov-Local Polynomial Models
This study proposes a data mining framework to discover qualitative and quantitative patterns in discrete-valued time series (DTS). In our method, there are three levels for mining similarity and periodicity patterns. At the first level, a structuralbased search based on distance measure models is employed to find pattern structures; the second level performs a value-based search on the discove...
متن کاملSpatio-temporal Analysis of Brain MRI Images Using Hidden Markov Models
A rapidly increasing number of medical imaging studies is longitudinal, i.e. involves series of repeated examinations of the same individuals. This paper presents a methodology for analysis of such 4D images, with brain aging as the primary application. An adaptive regional clustering method is first adopted to construct a spatial pattern, in which a measure of correlation between morphological...
متن کامل