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AMPLIFAI: A Multiphase CT Dataset for Benchmarking Clinical Reasoning in LI-RADS Assessment of Liver Lesions
Pranav Kulkarni, Nikhil Shah, Amritansh Suryavanshi +10
Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide, with early detection improving survival from <20% to >70%. The standardized Liver I…
Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following
Tianyi Xiong, Yi Ge, Ming Li +13
Large multimodal models (LMMs) are increasingly adopted as judges in multimodal evaluation systems due to their strong instruction following and consistency with human preferences.…
X-Mark: Saliency-Guided Robust Dataset Ownership Verification for Medical Imaging
Pranav Kulkarni, Junfeng Guo, Heng Huang
High-quality medical imaging datasets are essential for training deep learning models, but their unauthorized use raises serious copyright and ethical concerns. Medical imaging pre…
From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification
Pranav Kulkarni, Adway Kanhere, Paul H. Yi +1
Federated learning (FL) is a promising paradigm to collaboratively train a global chest x-ray (CXR) classification model using distributed datasets while preserving patient privacy…
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification
Skylar Chan, Pranav Kulkarni, Paul H. Yi +1
Quantum machine learning (QML) has the potential for improving the multi-label classification of rare, albeit critical, diseases in large-scale chest x-ray (CXR) datasets due to th…