A GMM-based embedding remix technique generates augmented patients for data-scarce medical MIL, improving performance in missing-class and low-data regimes.
IEEE Transactions on Med- ical Imaging43(5), 1841–1852 (2024)
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Re-mixing Embeddings for Patient Augmentation in Data Scarce Multiple Instance Learning
A GMM-based embedding remix technique generates augmented patients for data-scarce medical MIL, improving performance in missing-class and low-data regimes.