Name
Abstract | ||
|---|---|---|
We evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s13326-018-0177-x | J. Biomedical Semantics |
Keywords | Field | DocType |
Biomedical ontology,Hypothesis testing,Incomplete knowledge,Network analysis,Ontology mapings | Data science,Incomplete knowledge,Causality,Computer science,Statistical hypothesis testing | Journal |
Volume | Issue | ISSN |
9 | 1 | 2041-1480 |
Citations | PageRank | References |
1 | 0.37 | 26 |
Authors | ||
11 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Asan Agibetov | 1 | 6 | 2.15 |
| Ernesto Jiménez-Ruiz | 2 | 1120 | 84.14 |
| Marta Ondresik | 3 | 1 | 0.37 |
| Alessandro Solimando | 4 | 41 | 5.48 |
| Imon Banerjee | 5 | 48 | 11.45 |
| Giovanna Guerrini | 6 | 705 | 97.44 |
| Chiara Eva Catalano | 7 | 78 | 11.94 |
| Joaquim Miguel Oliveira | 8 | 2 | 0.75 |
| Giuseppe Patanè | 9 | 163 | 17.87 |
| Rui Luis Reis | 10 | 2 | 1.42 |
| Michela Spagnuolo | 11 | 1496 | 95.81 |