ArticleScientific reports2018
An Epidemiological Human Disease Network Derived from Disease Co-occurrence in Taiwan.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and meta-analysis of disease clusters in multimorbidity.Nature communications · 2025Pooled it
- Patient stratification reveals the molecular basis of disease co-occurrences.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Complex networks approach to study comorbidities in patients with unruptured intracranial aneurysms.Scientific reports · 2024Article
- Patterns of Outpatient Phecodes Predating the Diagnosis of Systemic Lupus Erythematosus in Taiwanese Women.Journal of clinical medicine · 2022Article
- The effect of disease co-occurrence measurement on multimorbidity networks: a population-based study.BMC medical research methodology · 2022Article
- Nature and Extent of Physical Comorbidities Among Korean Patients With Mental Illnesses: Pairwise and Network Analysis Based on Health Insurance Claims Data.Psychiatry investigation · 2022Article
- Age- and Sex-Specific Differences in Multimorbidity Patterns and Temporal Trends on Assessing Hospital Discharge Records in Southwest China: Network-Based Study.Journal of medical Internet research · 2022Article
- Visualizing COVID-19 pandemic risk through network connectedness.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Review
- PedMap: a pediatric diseases map generated from clinical big data from Hangzhou, China.Scientific reports · 2019Article
- Air pollution as cause of mental disease: Appraisal of the evidence.PLoS biology · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In "classic" biomedical research, diseases have usually been studied individually. The pioneering human disease network (HDN) studies jointly consider a large number of diseases, analyse their interconnections, and provide a more comprehensive description of diseases. However, most of the existing HDN studies are based on molecular information and can only partially describe disease interconnections. Building on the unique Taiwan National Health Insurance Research Database (NHIRD), in this study, we construct the epidemiological HDN (eHDN), where two diseases are concluded as interconnected if their observed probability of co-occurrence deviating that expected under independence. Advancing from the existing HDN, the eHDN can also accommodate non-molecular connections and have more important practical implications. Building on the network construction, we examine important network properties such as connectivity, module, hub, and others and describe their temporal patterns. This study is among the first to systematically construct the eHDN and can have important implications for human disease research and health care and management.
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