Statistical methods for constructing disease comorbidity networks from longitudinal inpatient data
Abstract Tools from network science can be utilized to study relations between diseases. Different studies focus on different types of inter-disease linkages. One of them is the comorbidity patterns derived from large-scale longitudinal data of hospital discharge records. Researchers seek to describ...
Main Authors: | Babak Fotouhi, Naghmeh Momeni, Maria A. Riolo, David L. Buckeridge |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2018-11-01
|
Series: | Applied Network Science |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1007/s41109-018-0101-4 |
Similar Items
-
Statistical methods for constructing disease comorbidity networks from longitudinal inpatient data
by: Fotouhi, Babak, et al.
Published: (2018) -
Quantifying the Effect of Community Structures for Link Prediction by Constructing Null Models
by: Xiao-Ke Xu, et al.
Published: (2020-01-01) -
Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data
by: Narayan Sharma, et al.
Published: (2021-01-01) -
Bitcoin Transaction Networks: An Overview of Recent Results
by: Nicoló Vallarano, et al.
Published: (2020-12-01) -
Network analysis of autistic disease comorbidities in Chinese children based on ICD-10 codes
by: Xiaojun Li, et al.
Published: (2020-10-01)