14 citations · 18 across the 8 of their papers we have counts for
8 papers
A Knowledge-Informed Large Language Model Framework for U.S. Nuclear Power Plant Shutdown Initiating Event Classification for Probabilistic Risk Assessment
Min Xian, Tao Wang, Sai Zhang +2
Identifying and classifying shutdown initiating events (SDIEs) is critical for developing low power shutdown probabilistic risk assessment for nuclear power plants. Existing comput…
Causality Extraction from Nuclear Licensee Event Reports Using a Hybrid Framework
Shahidur Rahoman Sohag, Sai Zhang, Min Xian +3
Industry-wide nuclear power plant operating experience is a critical source of raw data for performing parameter estimations in reliability and risk models. Much operating experien…
A2DMN: Anatomy-Aware Dilated Multiscale Network for Breast Ultrasound Semantic Segmentation
Kyle Lucke, Aleksandar Vakanski, Min Xian
In recent years, convolutional neural networks for semantic segmentation of breast ultrasound (BUS) images have shown great success; however, two major challenges still exist. 1) M…
Post-Hoc Explainability of BI-RADS Descriptors in a Multi-task Framework for Breast Cancer Detection and Segmentation
Mohammad Karimzadeh, Aleksandar Vakanski, Min Xian +1
Despite recent medical advancements, breast cancer remains one of the most prevalent and deadly diseases among women. Although machine learning-based Computer-Aided Diagnosis (CAD)…
Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network
Bryar Shareef, Min Xian, Aleksandar Vakanski +1
Capturing global contextual information plays a critical role in breast ultrasound (BUS) image classification. Although convolutional neural networks (CNNs) have demonstrated relia…
Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model
Fenghe Tang, Jianrui Ding, Lingtao Wang +2
Medical image segmentation is a critical step in computer-aided diagnosis, and convolutional neural networks are popular segmentation networks nowadays. However, the inherent local…