Figure 1
From: Quantifying deep neural network uncertainty for atrial fibrillation detection with limited labels
A hypothetical example of how uncertainty estimates can help in interpreting ML model predictions. Here, an AF or sinus rhythm classifier is generating probability estimates for short segments of continuous ECG data. Adding an uncertainty estimate allows us to highlight the transition between different rhythm types, as shown in the raw (unprocessed) signal in red. Depending on the use case, these transition periods could be flagged for further inspection or ignored in favour of less ambiguous time intervals.
