Tsinghua–Berkeley Shenzhen Institute

Emergence of New Disease: How Can Artificial Intelligence Help?

Yurim Park, Daniel Casey, Indra Joshi et al.

2020 · 53 Zit.

Efficiency, accuracy, and health professional's perspectives regarding artificial intelligence in radiology practice: A scoping review

Chanchan He, Weiqi Liu, Jing Xu et al.

2024 · 17 Zit.

Realizing the Potential of Computer-Assisted Surgery by Embedding Digital Twin Technology

Jiaxin Qin, Jian Wu

2022 · 11 Zit.

Pathology diagnosis of intraoperative frozen thyroid lesions assisted by deep learning

Tingting He, Shanshan Shi, Yiqing Liu et al.

2024 · 8 Zit.

Comment on: “From conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy”

Zhimin Du

2025 · 1 Zit.

Structured clinical approach to enable large language models to be used for improved clinical diagnosis and explainable reasoning

Muhammad Ayoub, Hai Zhao, Lifeng Li et al.

2026 · 0 Zit.

Diffusional magnetic resonance imaging anonymizing with variational autoencoder

Yunheng Shen, Ling Zheng, Ruohan Liu et al.

2026 · 0 Zit.

AI agent in healthcare: applications, evaluations, and future directions

Lina Zhao, Shengrui Liu, Tangsiwei Xin et al.

2026 · 0 Zit.

Abstract B024: Artificial intelligence enables the ethical reconstruction and social value realization of global cancer research: From technological innovation to humanistic care

Zhimin Du, Lijin Lian, Xi Wang et al.

2025 · 0 Zit.

ICAS: Detecting Training Data from Autoregressive Image Generative Models

Hongyao Yu, Yixiang Qiu, Yiheng Yang et al.

2025 · 0 Zit.

Concerns about artificial intelligence feedback validation in the 2-Sigma platform

Zhimin Du

2026 · 0 Zit.

Addressing algorithmic bias in artificial intelligence-driven medical education assessment

Zhimin Du

2026 · 0 Zit.