Name
Abstract | ||
|---|---|---|
BackgroundThe adoption in oncology of Clinical Decision Support (CDS) may help clinical users to efficiently deal with the high complexity of the domain, lead to improved patient outcomes, and reduce the current knowledge gap between clinical research and practice. While significant effort has been invested in the implementation of CDS, the uptake in the clinic has been limited. The barriers to adoption have been extensively discussed in the literature. In oncology, current CDS solutions are not able to support the complex decisions required for stratification and personalized treatment of patients and to keep up with the high rate of change in therapeutic options and knowledge. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12911-016-0314-3 | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Clinical decision support, Clinical workflows, Knowledge models, CDS adoption, Oncology | Oncology,Data mining,Precision medicine,Internal medicine,Knowledge management,Clinical research,Clinical decision support system,Health informatics,Medicine,Workflow | Journal |
Volume | Issue | ISSN |
16 | S-2 | 1472-6947 |
Citations | PageRank | References |
1 | 0.38 | 10 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anca I. D. Bucur | 1 | 167 | 20.83 |
| Jasper van Leeuwen | 2 | 21 | 7.63 |
| Nikolaos Christodoulou | 3 | 1 | 0.38 |
| Kamana Sigdel | 4 | 34 | 3.59 |
| Katerina Argyri | 5 | 1 | 0.38 |
| Lefteris Koumakis | 6 | 91 | 21.25 |
| Norbert Graf | 7 | 87 | 17.28 |
| Georgios S. Stamatakos | 8 | 33 | 10.84 |