ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2014
New genetic variants improve personalized breast cancer diagnosis.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2014. 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.
- Integrating hypertension phenotype and genotype with hybrid non-negative matrix factorization.Bioinformatics (Oxford, England) · 2019Article
- Recursive Feature Elimination by Sensitivity Testing.Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications · 2018Article
- Temporal Poisson Square Root Graphical Models.Proceedings of machine learning research · 2018Article
- Utility of Genetic Testing in Addition to Mammography for Determining Risk of Breast Cancer Depends on Patient Age.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Structure-Leveraged Methods in Breast Cancer Risk Prediction.Journal of machine learning research : JMLR · 2016Article
- Discriminatory power of common genetic variants in personalized breast cancer diagnosis.Proceedings of SPIE--the International Society for Optical Engineering · 2016Article
- Breast Imaging in the Era of Big Data: Structured Reporting and Data Mining.AJR. American journal of roentgenology · 2016Article
- Breast Cancer Prognostics Using Multi-Omics Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Developing a utility decision framework to evaluate predictive models in breast cancer risk estimation.Journal of medical imaging (Bellingham, Wash.) · 2015Article
- Developing a clinical utility framework to evaluate prediction models in radiogenomics.Proceedings of SPIE--the International Society for Optical Engineering · 2015Article
- Applying computation biology and "big data" to develop multiplex diagnostics for complex chronic diseases such as osteoarthritis.Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals · 2015Review
- Comparing the value of mammographic features and genetic variants in breast cancer risk prediction.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Recent large-scale genome-wide association studies (GWAS) have identified a number of new genetic variants associated with breast cancer. However, the degree to which these genetic variants improve breast cancer diagnosis in concert with mammography remains unknown. We conducted a case-control study and collected mammography features and 77 genetic variants which reflect the state of the art GWAS findings on breast cancer. A naïve Bayes model was developed on the mammography features and these genetic variants. We observed that the incorporation of the genetic variants significantly improved breast cancer diagnosis based on mammographic findings.
Identifiers
25717406PMC4333695What OpenQuestion holds
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.