no code implementations • 28 Apr 2024 • Zesheng Hong, Yubiao Yue, Yubin Chen, Huanjie Lin, Yuanmei Luo, Mini Han Wang, Weidong Wang, Jialong Xu, Xiaoqi Yang, Zhenzhang Li, Sihong Xie
Recently, research has explored various out-of-distribution (OOD) detection situations and techniques to enable a trustworthy medical AI system.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
1 code implementation • 6 Mar 2024 • Yubiao Yue, Zhenzhang Li
To demonstrate the potential of MedMamba, we conducted extensive experiments using 14 publicly available medical datasets with different imaging techniques and two private datasets built by ourselves.
no code implementations • 10 Oct 2023 • Yubiao Yue, Zhenzhang Li
In addition, we demonstrated the drawbacks of classification models and buttressed the potential of MIM through clinical validation.
no code implementations • 31 Aug 2023 • Yubiao Yue, Jun Xue, Haihua Liang, Bingchun Luo, Zhenzhang Li
The objective of this work is to diagnose cervical lymph node lesions in ultrasound images by leveraging a deep learning model.
no code implementations • 27 Aug 2023 • Yubiao Yue, Jun Xue, Chao Wang, Haihua Liang, Zhenzhang Li
Our findings suggest U-SEANNet is the state-of-the-art model for nasal diseases diagnosis in endoscopic images.
no code implementations • 25 Aug 2023 • Yubiao Yue, Xiaoqiang Shi, Li Qin, Xinyue Zhang, Yanmei Chen, Jialong Xu, Zipei Zheng, Yujun Cao, Di Liu, Zhenzhang Li, Yang Li
Due to the lack of more efficient diagnostic tools for monkeypox, its spread remains unchecked, presenting a formidable challenge to global health.
no code implementations • 21 Aug 2023 • Yubiao Yue, Xinyu Zeng, Xiaoqiang Shi, Meiping Zhang, Fan Zhang, Yunxin Liang, Yan Liu, Zhenzhang Li, Yang Li
Deep learning-based ear disease diagnosis technology has proven effective and affordable.
no code implementations • 17 Mar 2023 • Yubiao Yue, Minghua Jiang, Xinyue Zhang, Jialong Xu, Huacong Ye, Fan Zhang, Zhenzhang Li, Yang Li
With the help of the Internet and communication terminal, Mpox-AISM can perform a real-time, low-cost, and convenient diagnosis for earlier-stage mpox in various real-world settings, thereby effectively curbing the spread of mpox virus.