most citedTransformer-Based Hematological Malignancy Prediction from Peripheral Blood Smears in a Real-World Cohort

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cs.LG2026

Re-mixing Embeddings for Patient Augmentation in Data Scarce Multiple Instance Learning

Muhammed Furkan Dasdelen, Fatih Ozlugedik, Anastasia Litinetskaya +3

Data scarcity is a major bottleneck in medical Multiple Instance Learning (MIL), especially for rare diseases or expensive modalities. We introduce a statistically grounded patient…