ArticleScientific reports2017
Network-based analysis of diagnosis progression patterns using claims data.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- A systematic review and meta-analysis of disease clusters in multimorbidity.Nature communications · 2025Pooled it
- Surgical Urgency and Perioperative Mortality: A National Analysis Using Procedure-specific Classification.Anesthesiology · 2026Article
- Temporal multimorbidity patterns and cluster identification: a longitudinal analysis of administrative data.BMC medicine · 2025Article
- Article
- Comorbidity Networks From Population-Wide Health Data: Aggregated Data of 8.9M Hospital Patients (1997-2014).Scientific data · 2025Article
- A network-based approach to explore comorbidity patterns among community-dwelling older adults living alone.GeroScience · 2024Article
- Unraveling cradle-to-grave disease trajectories from multilayer comorbidity networks.NPJ digital medicine · 2024Article
- Conceptualised psycho-medical footprint for health status outcomes and the potential impacts for early detection and prevention of chronic diseases in the context of 3P medicine.The EPMA journal · 2023Article
- Analysis of age-dependent gene-expression in human tissues for studying diabetes comorbidities.Scientific reports · 2023Article
- Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.iScience · 2023Article
- Revealing the dynamic landscape of drug-drug interactions through network analysis.Frontiers in pharmacology · 2023Article
- Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach.Scientific reports · 2022Article
- The Use of a Network Analysis to Identify Associations and Temporal Patterns Among Non-communicable Diseases in Japan Based on a Large Medical Claims Database.Drugs - real world outcomes · 2022Article
- Network-medicine framework for studying disease trajectories in U.S. veterans.Scientific reports · 2022Article
- Network-Based Methods for Approaching Human Pathologies from a Phenotypic Point of View.Genes · 2022Review
- 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
- Patient-centric characterization of multimorbidity trajectories in patients with severe mental illnesses: A temporal bipartite network modeling approach.Journal of biomedical informatics · 2022Article
- Impact of differential copayment on patient healthcare choice: evidence from South Korean National Cohort Study.BMJ open · 2021Article
- Network analysis of autistic disease comorbidities in Chinese children based on ICD-10 codes.BMC medical informatics and decision making · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.