38 citations · 71 across the 10 of their papers we have counts for
10 papers
AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis
Townim F. Chowdhury, Vu Minh Hieu Phan, Kewen Liao +5
The integration of vision-language models such as CLIP and Concept Bottleneck Models (CBMs) offers a promising approach to explaining deep neural network (DNN) decisions using conc…
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?
Yutong Xie, Qi Chen, Sinuo Wang +7
Current vision-language pre-training (VLP) methodologies predominantly depend on paired image-text datasets, a resource that is challenging to acquire in radiology due to privacy c…
CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation
Townim Faisal Chowdhury, Kewen Liao, Vu Minh Hieu Phan +7
Deep Neural Networks (DNNs) are widely used for visual classification tasks, but their complex computation process and black-box nature hinder decision transparency and interpretab…
Decomposing Disease Descriptions for Enhanced Pathology Detection: A Multi-Aspect Vision-Language Pre-training Framework
Vu Minh Hieu Phan, Yutong Xie, Yuankai Qi +7
Medical vision language pre-training (VLP) has emerged as a frontier of research, enabling zero-shot pathological recognition by comparing the query image with the textual descript…
A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?
Qiaozhu Mei, Yutong Xie, Walter Yuan +1
We administer a Turing Test to AI Chatbots. We examine how Chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairnes…
Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation
Qingjie Zeng, Yutong Xie, Zilin Lu +3
Annotation scarcity has become a major obstacle for training powerful deep-learning models for medical image segmentation, restricting their deployment in clinical scenarios. To ad…