Why the study?
Do active learning strategies improve the accuracy of ECG signal classification while minimizing the number of labeled samples?
Do active learning strategies improve the accuracy of ECG signal classification while minimizing the number of labeled samples?
Active learning strategies based on support vector machines can effectively boost ECG classification accuracy while reducing the need for large manually labeled datasets.
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May reduce labeling needs for ECG classifiers; leaves open real-world diagnostic impact pending validation.
Pasolli et al. (2010) studied this question.
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