Clinical diagnostics and patient stratification for use in the dental office
Personalized Oral Health Care: From Concept Design to Clinical Practice, Page: 61-72
2016
- 1Citations
- 11Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Book Chapter Description
Diagnostics and prognostics in dentistry can be applied to stratify patients according to risk for individualized disease forecasting and, ultimately, targeting resources to maximize health outcomes. Traditional clinical measures of periodontal disease show a history of tissue destruction but are unable to determine biologic onset or initiation of infl ammation and fail to predict susceptibility to or progression of disease. The state of the art in periodontal diagnostics is point-of-care (POC) periodontal methods (use of microbial, protein biomarker, and genetic measures). POC methods may use lab-on-a-chip (LOC) devices to analyze oral fl uids such as saliva. This technology can be applied for patient risk stratifi cation and predictive modeling to optimize personalized care in the dental offi ce to target healthcare resources to those at highest risk.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84960222724&origin=inward; http://dx.doi.org/10.1007/978-3-319-23297-3_5; http://link.springer.com/10.1007/978-3-319-23297-3_5; https://dx.doi.org/10.1007/978-3-319-23297-3_5; https://link.springer.com/chapter/10.1007/978-3-319-23297-3_5
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know