Spot the Biased Label in the Patient Reminder Model
Identify where model bias can enter through historical labels, missing populations, and average-only evaluation.
modern clinic operations room with a manager and analyst reviewing a laptop, appointment calendar board on a wall, patient folders and a transit map on a side table, clean medical office setting with room for overlay, no text, words, letters, numerals, logos. A clinic team reviews a no-show prediction model. The old no-show label includes appointments during a transit disruption, some walk-in and interpreter-assisted visits were left out of the dataset, and the team has only checked overall accuracy so far. The reminder policy goes to the medical directors tomorrow. Where could bias enter this patient reminder model? No-show label…
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