ArticleJournal of biomedical informatics2009
Integration of prostate cancer clinical data using an ontology.
Article in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Predictors of new persistent opioid use after surgery in adults.Anesthesiology and perioperative science · 2025Article
- PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data.Briefings in bioinformatics · 2024Article
- Infrastructure tools to support an effective Radiation Oncology Learning Health System.Journal of applied clinical medical physics · 2023Article
- Identification of Key Elements in Prostate Cancer for Ontology Building via a Multidisciplinary Consensus Agreement.Cancers · 2023Article
- Application of informatics in cancer research and clinical practice: Opportunities and challenges.Cancer innovation · 2022Review
- Analysis and visualization of disease courses in a semantically-enabled cancer registry.Journal of biomedical semantics · 2017Article
- Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research.Advances in nutrition (Bethesda, Md.) · 2017Review
- An information model for computable cancer phenotypes.BMC medical informatics and decision making · 2016Article
- An integrated, ontology-driven approach to constructing observational databases for research.Journal of biomedical informatics · 2015Article
- Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank.Journal of biomedical semantics · 2012Article
- Using semantic web technologies for cohort identification from electronic health records for clinical research.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2012Article
- A Case-based Retrieval System using Natural Language Processing and Population-based Visualization.Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology · 2011Article
- Semantically enabled and statistically supported biological hypothesis testing with tissue microarray databases.BMC bioinformatics · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
It is increasingly important for investigators to efficiently and effectively access, interpret, and analyze the data from diverse biological, literature, and annotation sources in a unified way. The heterogeneity of biomedical data and the lack of metadata are the primary sources of the difficulty for integration, presenting major challenges to effective search and retrieval of the information. As a proof of concept, the Prostate Cancer Ontology (PCO) is created for the development of the Prostate Cancer Information System (PCIS). PCIS is applied to demonstrate how the ontology is utilized to solve the semantic heterogeneity problem from the integration of two prostate cancer related database systems at the Fox Chase Cancer Center. As the results of the integration process, the semantic query language SPARQL is applied to perform the integrated queries across the two database systems based on PCO.
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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.