Abstract: A method includes generating, using at least one processor of an electronic device, a plurality of expert labels for a sample using a plurality of machine learned classifiers. The method also includes determining, using the at least one processor, an expert consensus label among the plurality of expert labels. The method further includes comparing, using the at least one processor, the expert consensus label to a ground truth label associated with the sample in response to determining that a consensus is found among the plurality of machine learned classifiers. The method also includes identifying, using the at least one processor, the ground truth label as a clean label in response to determining that the expert consensus label and the ground truth label match. In addition, the method includes identifying, using the at least one processor, the ground truth label for reassessment in response to determining that the expert consensus label and the ground truth label do not match.