no code implementations • 14 Apr 2024 • Weimin WANG, Min Gao, Mingxuan Xiao, Xu Yan, Yufeng Li
To address the issues of limited samples, time-consuming feature design, and low accuracy in detection and classification of breast cancer pathological images, a breast cancer image classification model algorithm combining deep learning and transfer learning is proposed.
no code implementations • 12 Apr 2024 • Mingxuan Xiao, Yufeng Li, Xu Yan, Min Gao, Weimin WANG
To address the challenges of dependence on pathologists expertise and the time-consuming nature of achieving accurate breast pathological image classification, this paper introduces an approach utilizing convolutional neural networks (CNNs) for the rapid categorization of pathological images, aiming to enhance the efficiency of breast pathological image detection.
no code implementations • 11 Apr 2024 • Xu Yan, Weimin WANG, Mingxuan Xiao, Yufeng Li, Min Gao
This study introduces a pioneering approach to enhance survival prediction models for gastric and Colon adenocarcinoma patients.
no code implementations • 21 Feb 2024 • Mingxuan Xiao, Yan Xiao, Hai Dong, Shunhui Ji, Pengcheng Zhang
To our knowledge, RITFIS is the first framework designed to assess the robustness of LLM-based intelligent software against natural language inputs.
1 code implementation • 22 Aug 2023 • Mingxuan Xiao, Yan Xiao, Hai Dong, Shunhui Ji, Pengcheng Zhang
The widespread adoption of DNNs in NLP software has highlighted the need for robustness.