OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 02.05.2026, 01:22

Shuguang Hospital

6.761 Arbeiten260.937 Zitationen
Land: CNTyp: healthcare

Relevante Arbeiten

Meistzitierte Publikationen im Bereich Gesundheit & MedTech

Feature rearrangement based deep learning system for predicting heart failure mortality

Zhe Wang, Yiwen Zhu, Dongdong Li et al.

2020 · 46 Zit.

A bibliometrics analysis based on the application of artificial intelligence in the field of radiotherapy from 2003 to 2023

Minghe Lv, Yue Feng, Su Zeng et al.

2024 · 6 Zit.

A novel evaluation benchmark for medical LLMs illuminating safety and effectiveness in clinical domains

Shirui Wang, Zhihui Tang, Huaxia Yang et al.

2025 · 2 Zit.

Informative Artifacts in AI-Assisted Care

Zubing Mei, De Zheng, Maojun Ge

2023 · 1 Zit.

Advancing medical AI through benchmarking and competition for specialty triage

Chao Ding, Mengjie Bian, Minjia Yuan et al.

2026 · 0 Zit.

Comment on the clinical trial landscape of artificial intelligence applications in gastrointestinal endoscopy

Xin Chen, Yuren Zhang, Wanli Deng

2026 · 0 Zit.

Citation Hallucination Determines Success: An Empirical Comparison of Six Medical AI Research Systems

Xuefei Shi, Zhanxiao Tian, Shuping Tan et al.

2026 · 0 Zit.

Evaluation of DeepSeek-R1 and ChatGPT on the Chinese National Medical Licensing Examination: A Multi-Year Comparative Study

Xinran WANG, Ziwen LONG, Boran ZHU et al.

2025 · 0 Zit.

Acceptance of Artificial Intelligence in Clinical Practice Among Chinese Physicians: Nationwide Cross-Sectional Survey Using Extended Unified Theory of Acceptance and Use of Technology and Explainable Machine Learning

Xuefei Shi, Zhanxiao Tian, Qi Guo et al.

2026 · 0 Zit.

Mapping the application landscape of artificial intelligence in prostate cancer: a global bibliometric analysis

Yuang Wei, Zubing Mei, Chuang Xie et al.

2025 · 0 Zit.

Evaluation of DeepSeek-R1 and ChatGPT-4o on the Chinese national medical licensing examination: a multi-year comparative study

Xinran Wang, Ziwen Long, Boran Zhu et al.

2026 · 0 Zit.

Response to the Letter: “Methodological Concerns in Radiomics: Addressing Bias in LASSO and SHAP for Thyroid Tumor Analysis”

Ying Fu, Fang Mei, Liting Shi et al.

2025 · 0 Zit.