ArticleJournal of the American Medical Informatics Association : JAMIA2013
Defining a comprehensive verotype using electronic health records for personalized medicine.
Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
43 citing papers in PubMed.
- Replicating Cardiovascular Condition-Birth Month Associations.Scientific reports · 2016Trial
- Identification of Time-Series Pattern Marker in Its Application to Mortality Analysis of Pneumonia Patients in Intensive Care Unit.Journal of personalized medicine · 2024Article
- Information heterogeneity between progress notes by physicians and nurses for inpatients with digestive system diseases.Scientific reports · 2024Article
- Review
- Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping.Arteriosclerosis, thrombosis, and vascular biology · 2023Review
- Machine learning approaches for electronic health records phenotyping: a methodical review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Data-driven identification of heart failure disease states and progression pathways using electronic health records.Scientific reports · 2022Article
- Using Natural Language Processing Techniques to Detect Adverse Events From Progress Notes Due to Chemotherapy.Cancer informatics · 2022Article
- The use of real-world data in drug repurposing.Translational and clinical pharmacology · 2021Review
- Applications of artificial intelligence in drug development using real-world data.Drug discovery today · 2021Review
- Linking clinotypes to phenotypes and genotypes from laboratory test results in comprehensive physical exams.BMC medical informatics and decision making · 2021Article
- System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal Consideration.Molecular diagnosis & therapy · 2021Review
- Multiscale classification of heart failure phenotypes by unsupervised clustering of unstructured electronic medical record data.Scientific reports · 2020Article
- EHR phenotyping for research recruitment: Researcher, IRB, and physician perspectives on approaches to contacting patients.Journal of clinical and translational science · 2020Article
- Predictive, Personalized, Preventive and Participatory (4P) Medicine Applied to Telemedicine and eHealth in the Literature.Journal of medical systems · 2019Review
- Developing a portable natural language processing based phenotyping system.BMC medical informatics and decision making · 2019Article
- Patient perspectives on use of electronic health records for research recruitment.BMC medical research methodology · 2019Article
- Identifying Breast Cancer Distant Recurrences from Electronic Health Records Using Machine Learning.Journal of healthcare informatics research · 2019Article
- A Vision for Development and Utilization of High-Throughput Phenotyping and Big Data Analytics in Livestock.Frontiers in genetics · 2019Review
- Disease associations depend on visit type: results from a visit-wide association study.BioData mining · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The burgeoning adoption of electronic health records (EHR) introduces a golden opportunity for studying individual manifestations of myriad diseases, which is called 'EHR phenotyping'. In this paper, we break down this concept by: relating it to phenotype definitions from Johannsen; comparing it to cohort identification and disease subtyping; introducing a new concept called 'verotype' (Latin: vere = true, actually) to represent the 'true' population of similar patients for treatment purposes through the integration of genotype, phenotype, and disease subtype (eg, specific glucose value pattern in patients with diabetes) information; analyzing the value of the 'verotype' concept for personalized medicine; and outlining the potential for using network-based approaches to reverse engineer clinical disease subtypes.
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Registered trials
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.