Quantifying Uncertainty in Detecting Choroidal Metastases on MRI using Evolutionary Strategies

Uncertainty quantification is crucial for the practical implementation of AI in radiology, and this study demonstrates a method to quantify uncertainty for classifying small sets of radiological images using a small data training approach called Deep Neuroevolution (DNE).