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Clustering Interval-Censored Time-Series for Disease Phenotyping
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add explicit delayed-entry alignment modeling (ablation) | SubLign on synthetic sigmoid data · Synthetic sigmoid | ARI: 0.81 -> 0.94 | Helped |
| Add explicit delayed-entry alignment modeling (ablation) | SubLign on cubic-spline data, Incr · Cubic-spline synthetic data, Incr | ARI: 0.77 ± 0.10 -> 0.82 ± 0.17 | Helped |
| Add explicit delayed-entry alignment modeling (ablation) | SubLign on cubic-spline data, Any · Cubic-spline synthetic data, Any | ARI: 0.29 ± 0.10 -> 0.46 ± 0.12 | Helped |
| Add explicit delayed-entry alignment modeling (ablation) | SubLign on synthetic sigmoid data with 50% missing · Synthetic sigmoid, 50% missing | ARI: 0.789 ± 0.058 -> 0.813 ± 0.024 | Helped |
| Use SubLign instead of KMeans+Loss | Synthetic sigmoid clustering · Synthetic sigmoid | ARI: 0.67 -> 0.94 | Helped |
| Use SubLign to infer alignment | HF artificially censored test data · HF artificially censored test data | correct recovery of δ' > δ'': 57.8 ± 4% -> 71% ± 2% | Helped |
| Use SubLign rather than SubNoLign (ablation) | Synthetic sigmoid data with no missing observations · Synthetic sigmoid, 0% missing | ARI: 0.809 ± 0.382 -> 0.980 ± 0.000 | Helped |
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