Aligning Subjective Ratings in Clinical Decision Making
This addresses the challenge of integrating subjective and objective data in clinical decision-making for patients at risk of Psoriatic Arthritis, though it is incremental as it applies existing pairwise ranking methods to a new domain.
The paper tackled the problem of aligning subjective expert ratings with objective clinical indicators to improve diagnosis, resulting in a new score that increased classification accuracy for detecting Psoriatic Arthritis presence/absence.
In addition to objective indicators (e.g. laboratory values), clinical data often contain subjective evaluations by experts (e.g. disease severity assessments). While objective indicators are more transparent and robust, the subjective evaluation contains a wealth of expert knowledge and intuition. In this work, we demonstrate the potential of pairwise ranking methods to align the subjective evaluation with objective indicators, creating a new score that combines their advantages and facilitates diagnosis. In a case study on patients at risk for developing Psoriatic Arthritis, we illustrate that the resulting score (1) increases classification accuracy when detecting disease presence/absence, (2) is sparse and (3) provides a nuanced assessment of severity for subsequent analysis.