In collaboration with Charite-Berlin Hospital, we are studying the drivers of variability in doctor performance when diagnosing ailments in dental x-ray images, and how multiple human-labelings of the same data can yield more reliable diagnoses of ailments. These studies aim to provide new insights on improving clinical care and a better understanding biases and shortcomings in evaluating diagnostic imaging. Further, we want to understand if multiple-expert labelling can be used a proxy for clinical ground-truth which should have implications of how to test AI algorithms in medical imaging in general.
