Name
Abstract | ||
|---|---|---|
People increasingly use the Internet for obtaining information regarding diseases, diagnoses and available treatments. Currently, many online health portals already provide non-personalized health information in the form of articles. However, it can be challenging to find information relevant to one's condition, interpret this in context, and understand the medical terms and relationships. Recommender Systems (RS) already help these systems perform precise information filtering. In this short paper, we look one step ahead and show the progress made towards RS helping users find personalized, complex medical interventions or support them with preventive healthcare measures. We identify key challenges that need to be addressed for RS to offer the kind of decision support needed in high-risk domains like healthcare. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3079452.3079499 | DH |
Field | DocType | Citations |
Data science,Health care,Recommender system,World Wide Web,Psychological intervention,Decision support system,Preventive healthcare,Health informatics,Medicine,Medical diagnosis,The Internet | Conference | 8 |
PageRank | References | Authors |
0.70 | 22 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Schafer, H. | 1 | 14 | 3.40 |
| Santiago Hors-Fraile | 2 | 12 | 4.01 |
| Raghav Pavan Karumur | 3 | 31 | 3.08 |
| André Calero Valdez | 4 | 134 | 25.44 |
| Alan Said | 5 | 334 | 37.52 |
| Helma Torkamaan | 6 | 11 | 4.97 |
| Tom Ulmer | 7 | 8 | 1.71 |
| Christoph Trattner | 8 | 466 | 44.79 |