Research map / Reinforcement learning / Visual and representation RL
Context-Aware Symptom Checking for Disease Diagnosis Using Hierarchical Reinforcement Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| hierarchical master model over anatomical part models vs single best part model | symptom checker · Task 1 (SymCAT simulated) | top-1 accuracy: 48.12 -> 63.55 | Helped |
| hierarchical master model | symptom checker · Task 4 (SymCAT simulated) | top-1 accuracy: 21.24 -> 26.26 | Helped |
| hierarchical master model | symptom checker · Task 4 | #inquiry steps: 6.94 -> 5.01 | Helped |
| hierarchical master model | symptom checker · Task 1 | #inquiry steps: 7.17 -> 7.15 | No clear effect |
| add context-aware policy transformation (age, gender) (ablation) | Hierarchical Model · Task 1 context-influenced diseases | top-5 accuracy: 76.16 -> 83.62 | Helped |
| add context-aware policy transformation (age, gender) (ablation) | Hierarchical Model · Task 3 context-influenced diseases | top-5 accuracy: 32.18 -> 36.58 | Helped |
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