Unknown

Dataset Information

0

Network-based analysis of diagnosis progression patterns using claims data.


ABSTRACT: In recent years, several network models have been introduced to elucidate the relationships between diseases. However, important risk factors that contribute to many human diseases, such as age, gender and prior diagnoses, have not been considered in most networks. Here, we construct a diagnosis progression network of human diseases using large-scale claims data and analyze the associations between diagnoses. Our network is a scale-free network, which means that a small number of diagnoses share a large number of links, while most diagnoses show limited associations. Moreover, we provide strong evidence that gender, age and disease class are major factors in determining the structure of the disease network. Practically, our network represents a methodology not only for identifying new connectivity that is not found in genome-based disease networks but also for estimating directionality, strength, and progression time to transition between diseases considering gender, age and incidence. Thus, our network provides a guide for investigators for future research and contributes to achieving precision medicine.

SUBMITTER: Jeong E 

PROVIDER: S-EPMC5686166 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications

Network-based analysis of diagnosis progression patterns using claims data.

Jeong Eugene E   Ko Kyungmin K   Oh Seungbin S   Han Hyun Wook HW  

Scientific reports 20171114 1


In recent years, several network models have been introduced to elucidate the relationships between diseases. However, important risk factors that contribute to many human diseases, such as age, gender and prior diagnoses, have not been considered in most networks. Here, we construct a diagnosis progression network of human diseases using large-scale claims data and analyze the associations between diagnoses. Our network is a scale-free network, which means that a small number of diagnoses share  ...[more]

Similar Datasets

| S-EPMC6519085 | biostudies-literature
| S-EPMC6812739 | biostudies-literature
| S-EPMC8578343 | biostudies-literature
| S-EPMC7106695 | biostudies-literature
| S-EPMC8176093 | biostudies-literature
| S-EPMC5803484 | biostudies-literature
| S-EPMC6556828 | biostudies-literature
| S-EPMC7672137 | biostudies-literature
| S-EPMC9401144 | biostudies-literature
| S-EPMC6955498 | biostudies-literature