Attia MI

A global increase in the prevalence of obesity and type 2 diabetes is strongly connected to an increased prevalence of non-alcoholic fatty liver disease (NAFLD) worldwide. In this article, the progression of the NAFLD process is modeled by continuous time Markov chains (CTMCs) with nine states. Maximum likelihood is used to estimate the transition intensities among the states. Once the transition intensities are obtained, the mean sojourn time and its variance are estimated, and the state probability distribution and its asymptotic covariance matrix are also estimated.

Dataset Files

You must be an IEEE Dataport Subscriber to access these files. Subscribe now or login.

Documentation: 
AttachmentSize
File fams-07-766085.pdf612.19 KB
[1] Iman Mohammed Attia Abd El-Khalik Abo-Elreesh, "CTMC Analyzing NAFLD Progression (big Model)", IEEE Dataport, 2022. [Online]. Available: http://dx.doi.org/10.21227/0h9c-9283. Accessed: Feb. 29, 2024.
@data{0h9c-9283-22,
doi = {10.21227/0h9c-9283},
url = {http://dx.doi.org/10.21227/0h9c-9283},
author = {Iman Mohammed Attia Abd El-Khalik Abo-Elreesh },
publisher = {IEEE Dataport},
title = {CTMC Analyzing NAFLD Progression (big Model)},
year = {2022} }
TY - DATA
T1 - CTMC Analyzing NAFLD Progression (big Model)
AU - Iman Mohammed Attia Abd El-Khalik Abo-Elreesh
PY - 2022
PB - IEEE Dataport
UR - 10.21227/0h9c-9283
ER -
Iman Mohammed Attia Abd El-Khalik Abo-Elreesh. (2022). CTMC Analyzing NAFLD Progression (big Model). IEEE Dataport. http://dx.doi.org/10.21227/0h9c-9283
Iman Mohammed Attia Abd El-Khalik Abo-Elreesh, 2022. CTMC Analyzing NAFLD Progression (big Model). Available at: http://dx.doi.org/10.21227/0h9c-9283.
Iman Mohammed Attia Abd El-Khalik Abo-Elreesh. (2022). "CTMC Analyzing NAFLD Progression (big Model)." Web.
1. Iman Mohammed Attia Abd El-Khalik Abo-Elreesh. CTMC Analyzing NAFLD Progression (big Model) [Internet]. IEEE Dataport; 2022. Available from : http://dx.doi.org/10.21227/0h9c-9283
Iman Mohammed Attia Abd El-Khalik Abo-Elreesh. "CTMC Analyzing NAFLD Progression (big Model)." doi: 10.21227/0h9c-9283