Forecasting New Cases of Bipolar Disorder Using Poisson Hidden Markov Model

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Alafchi Behnaz; YAZDI RAVANDI SAEID; NAJAFI VOSOUGH ROYA; GHALEIHA ALI; SADEGHIFAR MAJID

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: International Clinical Neuroscience Journal Year:2018 | Volume:5 | Issue:1 Page(s): 7-10

Download Full-Text

View:

134

Download:

Cites:

Information Journal Paper

Title

Forecasting New Cases of Bipolar Disorder Using Poisson Hidden Markov Model

Author(s)

Keywords

Bipolar Disorder

Forecast

Poisson hidden Markov model

Hamadan

Abstract

Background: Bipolar Disorder (BD) is a major public health problem. In time series count data there may be over dispersion, and serial dependency. In such situation some models that can consider the dependency are needed. The purpose current research was to use Poisson hidden Markov model to Forecast new monthly BD instances. Methods: In current study the dataset including the frequency of new instances of BD from October 2008 to March 2015 in Hamadan Province, the west of Iran were used. We used Poisson hidden Markov with different number of conditions to determine the best model according to Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Then we used final model to Forecast for the next 24 months. Results: Poisson hidden Markov with two states were chosen as the final model. Each component of dependent mixture model explained one of the states. The results showed that the new BD cases is increase over time and due to Forecasting results number of patients for the next 24 months comforted in state two with mean 85. 15. The Forecast interval was approximately (56, 100). Conclusion: As the Poisson hidden Markov models was not used to Forecast the future states in other prior researches, the findings of this study set forward a Forecasting strategy as an alternative to common methods, by considering its deficiencies.

Cites

Comparison of the Effectiveness of Cognitive Behavioral Therapy and Acceptance and Commitment Therapy on Reducing Mood Symptoms in Patients With Substance Abuse

References

Forecasting Schizophrenia Incidence Frequencies Using Time Series Approach

Cite

APA: Copy

Alafchi, Behnaz, YAZDI RAVANDI, SAEID, NAJAFI VOSOUGH, ROYA, GHALEIHA, ALI, & SADEGHIFAR, MAJID. (2018). Forecasting New Cases of Bipolar Disorder Using Poisson Hidden Markov Model. INTERNATIONAL CLINICAL NEUROSCIENCE JOURNAL, 5(1), 7-10. SID. https://sid.ir/paper/347807/en

Vancouver: Copy

Alafchi Behnaz, YAZDI RAVANDI SAEID, NAJAFI VOSOUGH ROYA, GHALEIHA ALI, SADEGHIFAR MAJID. Forecasting New Cases of Bipolar Disorder Using Poisson Hidden Markov Model. INTERNATIONAL CLINICAL NEUROSCIENCE JOURNAL[Internet]. 2018;5(1):7-10. Available from: https://sid.ir/paper/347807/en

IEEE: Copy

Behnaz Alafchi, SAEID YAZDI RAVANDI, ROYA NAJAFI VOSOUGH, ALI GHALEIHA, and MAJID SADEGHIFAR, “Forecasting New Cases of Bipolar Disorder Using Poisson Hidden Markov Model,” INTERNATIONAL CLINICAL NEUROSCIENCE JOURNAL, vol. 5, no. 1, pp. 7–10, 2018, [Online]. Available: https://sid.ir/paper/347807/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops