Knowledge graph · Trial
Machine Learning Model to Predict HOLS and Mortality After Discharge in Hospitalized Oncologic Patients
UNKNOWN
- Identifier
- CI-TRIAL-00060752
- Entity page
- /trial/NCT05534178 ↗
- Edges
- 2
- Neighbours
- 2 cancers
- Drawn
- 2 of 2 neighbours (cap 60); table lists every fetched edge
Accepted: cancer:<slug>, gene:<symbol>, variant:<slug>, drug:<slug>, trial:<NCT id>, or a bare CI id. Find slugs with search.
Most connectedLung Non-Small Cell Carcinoma 3,147Malignant Colorectal Neoplasm 1,866ABL1 298EGFR 276Imatinib 450Dasatinib 321
Neighbourhood
Radial view
Focus at the centre; neighbours grouped by entity type. Click a node to re-centre the graph on it; ↗ opens the entity page. Hover a spoke for relationship, evidence level, cancer context and source.
Edges
Every edge, grouped by relationship
Source-native edges first (aggregated per neighbour, direction, evidence level and source), then derived registry links. Up to 15 per relationship (10 trials); “show all” raises one group to 200.
| Relationship | Neighbour | Direction | Evidence level | Cancer context | Support | Claim | Source | Expand |
|---|---|---|---|---|---|---|---|---|
| Machine Learning Model to Predict HOLS and Mortality After Discharge in Hospitalized Oncologic Patients condition of …CONDITION_OFderived2 of 2 | ||||||||
| ← condition of | Neoplasm registry condition “Tumor” mapped ALIAS | — | — | Neoplasm | 1 | Observed | clinicaltrials | graph → |
| ← condition of | Solid Neoplasm registry condition “Solid Tumor” mapped CURATED_BROADER | — | — | |||||