Using binary silver labels in electronic health records-based computable phenotyping algorithms
Gold-standard phenotype labels are often unavailable at scale in electronic health record (EHR) studies because they require manual chart review. Weakly supervised phenotyping methods instead use silver-standard labels, such as diagnosis-code counts, natural language processing (NLP) mentions, medication indicators, or laboratory thresholds. PheNorm is widely used for this purpose, but its original formulation was designed for count-valued silver labels and relies on log transformation, utilization normalization, and Gaussian mixture modeling. These steps are not directly suited to binary silver labels, which are common and may be highly informative. We propose Binary PheNorm, an extensio...
| Authors | Shuhe Wang, Matthew T. Slaughter, Jennifer C. Nelson et al. |
|---|---|
| Primary category | stat.ME |
| Published | 20 July 2026 |
| Last updated at source | 20 July 2026 |
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