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Achieving over 5% improvement in ovarian segmentation accuracy by leveraging cross-modal insights from TVUS and MRI could redefine standards in medical imaging for endometriosis.
PhonoQ-derived features boost phonological classification accuracy, revealing intricate speech patterns that traditional models miss.
WING achieves state-of-the-art CT synthesis from MRI and CBCT by transforming the regression target into windowed representations, significantly improving detail and accuracy.
Ditch phoneme-based speech processing: directly predicting phonological features from speech unlocks substantial gains in multilingual and cross-lingual speech recognition.
