Zhiyuan Li

A clinical image classifier that returns a set of possible diagnoses does not guarantee that a severe case avoids a harmful action. HC-ROCP adds a harm penalty weighted by predicted severe-class probability to frozen classifier probabilities, tests coverage and severe-action error on disjoint calibration splits, and then certifies, reports descriptively, or refuses each claim. On COVID-19 radiographs across ten calibration seeds, severe-action errors fall from the exact ROCP baseline's 4.68% to 0.54%, at higher modeled loss.

A clinical image classifier that returns a set of possible diagnoses does not guarantee that a severe case avoids a harmful action. HC-ROCP adds a harm penalty weighted by predicted severe-class probability to frozen classifier probabilities, tests coverage and severe-action error on disjoint calibration splits, and then certifies, reports descriptively, or refuses each claim. On COVID-19 radiographs across ten calibration seeds, severe-action errors fall from the exact ROCP baseline's 4.68% to 0.54%, at higher modeled loss.