Patients in the mental health care system typically make more or less irregularly spaced visits to psychiatrists, both within and between episodes of a given illness. A Markov model is constructed which can predict the utilization of psychiatric services for such patients. Unlike previous Markov models of utilization, the current model takes as its starting point a model of an actual disease, specifically, endogenous depression It is shown how one can estimate the parameters of both the model of utilization and the model of depression using data which were collected for clinical research purposes. The models provide reasonable fits to the data. Several applications of the models are worked out. In addition to predicting the utilization of m...
This paper addresses the problem of modelling longitudinal data describing patients' responses in cl...
Unsupervised learning is often used to obtain insight into the underlying structure of medical data,...
Objectives: Longitudinal models describing the time course of the clinical endpoint in psychiatric t...
The most appropriate next step in depression treatment after the initial treatment fails is unclear....
Thesis (Master's)--University of Washington, 2016-06To assess and monitor the progression dynamics o...
Background/objective: To describe the design of 'DepMod', a health-economic Markov model for assessi...
Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidi...
The most appropriate next step in depression treatment after the initial treatment fails is unclear....
Markov chains (MCs) have been used to study how the health states of patients are progressing in tim...
Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidi...
Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidi...
International audienceBackgroundDepression is among the major contributors to worldwide disease burd...
Context: Mathematical models describing changes in mood in affective disorders may assist in the ide...
This paper addresses the problem of modelling longitudinal data describing patients' responses in cl...
Unsupervised learning is often used to obtain insight into the underlying structure of medical data,...
Objectives: Longitudinal models describing the time course of the clinical endpoint in psychiatric t...
The most appropriate next step in depression treatment after the initial treatment fails is unclear....
Thesis (Master's)--University of Washington, 2016-06To assess and monitor the progression dynamics o...
Background/objective: To describe the design of 'DepMod', a health-economic Markov model for assessi...
Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidi...
The most appropriate next step in depression treatment after the initial treatment fails is unclear....
Markov chains (MCs) have been used to study how the health states of patients are progressing in tim...
Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidi...
Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidi...
International audienceBackgroundDepression is among the major contributors to worldwide disease burd...
Context: Mathematical models describing changes in mood in affective disorders may assist in the ide...
This paper addresses the problem of modelling longitudinal data describing patients' responses in cl...
Unsupervised learning is often used to obtain insight into the underlying structure of medical data,...
Objectives: Longitudinal models describing the time course of the clinical endpoint in psychiatric t...