Name
Title | ||
|---|---|---|
A collaborative filtering approach to assess individual condition risk based on patients' social network data |
Abstract | ||
|---|---|---|
Healthcare research has shown that conditions are correlated with each other, for example, in patients with type-2 diabetes, chronic nephatony often results from diabetic nephropathy. This correlation is called comorbidity relationship. The comorbidity relationships are often so complex that it is difficult to comprehend them. A disease prediction model extending the collaborative filtering used in recommender systems was developed to use publicly available patients' social network data to predict such comorbidity relationships, and to help doctors as well as uninformed patients to assess potential health risks. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2649387.2660813 | BCB |
Keywords | DocType | Citations |
algorithms,recommender system,social computing,ehr,data mining | Conference | 1 |
PageRank | References | Authors |
0.37 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiang Ji | 1 | 34 | 4.46 |
| Soon Ae Chun | 2 | 893 | 100.67 |
| James Geller | 3 | 33 | 5.08 |