8 papers
Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification
Ha-Hieu Pham, Hai-Dang Nguyen, Dang P. M. Cao +5
In chest X-ray (CXR) classification, acceptable ranking performance can still leave rare-positive patients below threshold, especially within subgroups. We study this pre-deploymen…
CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification
Hexin Dong, Yi Lin, Pengyu Zhou +25
Chest X-ray (CXR) interpretation is hindered by the long-tailed distribution of pathologies and the open-world nature of clinical environments. Existing benchmarks often rely on cl…
Robust White Blood Cell Classification with Stain-Normalized Decoupled Learning and Ensembling
Luu Le, Hoang-Loc Cao, Ha-Hieu Pham +2
White blood cell (WBC) classification is fundamental for hematology applications such as infection assessment, leukemia screening, and treatment monitoring. However, real-world WBC…
Handling Supervision Scarcity in Chest X-ray Classification: Long-Tailed and Zero-Shot Learning
Ha-Hieu Pham, Hai-Dang Nguyen, Thanh-Huy Nguyen +4
Chest X-Ray (CXR) classification in clinical practice is often limited by imperfect supervision, arising from (i) extreme long-tailed multi-label disease distributions and (ii) mis…
FUGC: Benchmarking Semi-Supervised Learning Methods for Cervical Segmentation
Jieyun Bai, Yitong Tang, Zihao Zhou +36
Accurate segmentation of cervical structures in transvaginal ultrasound (TVS) is critical for assessing the risk of spontaneous preterm birth (PTB), yet the scarcity of labeled dat…
Graph-Theoretic Consistency for Robust and Topology-Aware Semi-Supervised Histopathology Segmentation
Ha-Hieu Pham, Minh Le, Han Huynh +2
Semi-supervised semantic segmentation (SSSS) is vital in computational pathology, where dense annotations are costly and limited. Existing methods often rely on pixel-level consist…