Towards a new generation of artificial intelligence in China
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Some existing AI tools for item generation are costly, need high technical support, and have good results.
“Some of these are costly, need high technical support, and have good results [24–27].”
From AI in medical education: uses of AI in construction type A MCQs (2024) · cites this paper as [24]
Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works
Cancer statistics in China, 2015
Chen, W., Zheng, R., Baade, P. D., Zhang, S., Zeng, H., Bray, F., Jemal, A., Yu, X. Q., & He, J. (2016) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21338 · Cited by 17,038 · see citing works
Artificial intelligence in radiology
Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. J. W. L. (2018) · Nature Reviews Cancer · doi:10.1038/s41568-018-0016-5 · Cited by 3,803 · see citing works
Ehteshami Bejnordi, B., Veta, M., Johannes van Diest, P., van Ginneken, B., Karssemeijer, N., Litjens, G., van der Laak, J. A. W. M., and the CAMELYON16 Consortium, Hermsen, M., Manson, Q. F., et al. (2017) · JAMA · doi:10.1001/jama.2017.14585 · Cited by 3,293 · see citing works
Self-citationTowards Federated Learning at Scale: System Design
Bonawitz, K., Eichner, H., Grieskamp, W., Huba, D., Ingerman, A., Ivanov, V., Kiddon, C., Konečný, J., Mazzocchi, S., McMahan, H. B., et al. (2019) · arXiv · doi:10.48550/arxiv.1902.01046 · Cited by 2,334 · see citing works
Artificial intelligence in cancer imaging: Clinical challenges and applications
Bi, W. L., Hosny, A., Schabath, M. B., Giger, M. L., Birkbak, N. J., Mehrtash, A., Allison, T., Arnaout, O., Abbosh, C., Dunn, I. F., et al. (2019) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21552 · Cited by 1,846 · see citing works
Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation
Papandreou, G., Chen, L.-C., Murphy, K. P., & Yuille, A. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.203 · Cited by 1,041 · see citing works
Heading toward Artificial Intelligence 2.0
Pan, Y. (2016) · Engineering · doi:10.1016/j.eng.2016.04.018 · Cited by 432 · see citing works
Self-citationHybrid-augmented intelligence: collaboration and cognition
Zheng, N., Liu, Z.-Y., Ren, P.-J., Ma, Y.-Q., Chen, S.-T., Yu, S.-Y., Xue, J.-R., Chen, B.-D., & Wang, F.-Y. (2017) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1700053 · Cited by 303 · see citing works
Challenges and opportunities: from big data to knowledge in AI 2.0
Zhuang, Y., Wu, F. Q., Chen, C., & Pan, Y. (2017) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1601883 · Cited by 218 · see citing works
Self-citationUncovering and Mitigating Algorithmic Bias through Learned Latent Structure
Amini, A., Soleimany, A. P., Schwarting, W., Bhatia, S. N., & Rus, D. (2019) · Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3306618.3314243 · Cited by 206 · see citing works
Current trends in the development of intelligent unmanned autonomous systems
Zhang, T., Li, Q., Zhang, C.-S., Liang, H.-W., Li, P., Wang, T.-M., Li, S., Zhu, Y.-L., & Wu, C. (2017) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1601650 · Cited by 184 · see citing works
Crowd intelligence in AI 2.0 era
Li, W., Wu, W., Wang, H., Cheng, X., Chen, H., Zhou, Z., & Ding, R. (2017) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1601859 · Cited by 114 · see citing works
Self-citationEthical Principles and Governance Technology Development of AI in China
Wu, W., Huang, T., & Гонг, K. (2020) · Engineering · doi:10.1016/j.eng.2019.12.015 · Cited by 113 · see citing works
Cross-media analysis and reasoning: advances and directions
Peng, Y., Zhu, W., Zhao, Y., Xu, C., Huang, Q., Lu, H., Zheng, Q., Huang, T., & Gao, W. (2017) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1601787 · Cited by 104 · see citing works
Hybrid-augmented intelligence： collaboration and cognition
Nanning, Zheng, Ziyi, -, L., Pengju, Ren, Yongqiang, Ma, Shitao, Chen, et al. (2017) · Frontiers of Information Technology & Electronic Engineering · Cited by 70 · see citing works
The Next Breakthroughs of Artificial Intelligence: The Interdisciplinary Nature of AI
Zhuang, Y., Cai, M., Li, X., Luo, X., Yang, Q., & Wu, F. Q. (2020) · Engineering · doi:10.1016/j.eng.2020.01.009 · Cited by 42 · see citing works
Self-citationChallenges and opportunities： from big data to knowledge in AI2.0
Yue-ting, Zhuang, Wu, Chun, ○., Chen, Yun-he, & Pan (2017) · Acta Scientiarum Naturalium Universitatis Sunyatseni · Cited by 38 · see citing works
Special issue on artificial intelligence 2.0
Pan, Y. (2017) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1710000 · Cited by 31 · see citing works
Self-citationLocal–Global Memory Neural Network for Medication Prediction
Song, J., Wang, Y., Tang, S., Zhang⋆, Y., Chen, Z., Zhang, Z. M., Zhang, T., & Wu, F. Q. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.2989364 · Cited by 31 · see citing works
Self-citationCrowd intelligence in AI 2.0 era
Wei, W., Li, Wenjun, et al. (2017) · Acta Scientiarum Naturalium Universitatis Sunyatseni · Cited by 25 · see citing works
Artificial Intelligence: Enabling Technology to Empower Society
Lyu, Y.-G. (2020) · Engineering · doi:10.1016/j.eng.2020.01.005 · Cited by 21 · see citing works
2018 special issue on artificial intelligence 2.0: theories and applications
Pan, Y. (2018) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1810000 · Cited by 20 · see citing works
Self-citationThe Chinese Approach to Artificial Intelligence: An Analysis of Policy and RegulationPreprint
Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., & Floridi, L. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3469784 · Cited by 18 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Using digital story writing as a pedagogy to develop AI literacy among primary students
Ng, D. T. K., Luo, W., Chan, H. M. Y., & Chu, S. K. W. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100054 · Cited by 266 · see citing works
Sindermann, C., Yang, H., Elhai, J. D., Yang, S., Quan, L., Li, M., & Montag, C. (2022) · Discover Psychology · doi:10.1007/s44202-022-00020-y · Cited by 175 · see citing works
Self-citationWang, F., King, R. B., Chai, C. S., & Zhou, Y. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00417-2 · Cited by 124 · see citing works
“…study is conducted within the Chinese higher education context, where the government has identified AI as a key area of focus and a part of the national strategy, prioritizing investments in AI research and development, education and training, and infrastructure development (Wu et al., 2020).”
BackgroundOfosu-Ampong, K. (2024) · Telematics and Informatics Reports · doi:10.1016/j.teler.2024.100127 · Cited by 81 · see citing works
Predicting the moral consideration of artificial intelligences
Pauketat, J. V. T., & Anthis, J. R. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107372 · Cited by 60 · see citing works
Bradley, F. (2022) · Journal of the Australian Library and Information Association · doi:10.1080/24750158.2022.2101911 · Cited by 47 · see citing works
“China’s New Generation Artificial Intelligence Development Plan incorporates ethical considerations, but also research funding and education (Roberts et al., 2021; Wu et al., 2020).”
BackgroundAI in medical education: uses of AI in construction type A MCQs
Rezigalla, A. A. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05250-3 · Cited by 36 · see citing works
Hundal, J., Jain, M., & McCollom, J. (2025) · AI in Precision Oncology · doi:10.1177/2993091x251384313 · Cited by 11 · see citing works
The Quandary in Data Protection and Rights to Privacy of AI Technology Adoption in Malaysia
Kamaruddin, S., Wan Rosli, W. R., Mohd Saufi, N. N., Mohammad, A. M., & Hamin, Z. (2021) · 2021 Innovations in Power and Advanced Computing Technologies (i-PACT) · doi:10.1109/i-pact52855.2021.9696803 · Cited by 6 · see citing works
- Authors
- Wu, F., Lu, C., Zhu, M., Chen, H., Zhu, J., Yu, K., Li, L., Li, M., Chen, Q., Li, X., Cao, X., Wang, Z., Zha, Z., Zhuang, Y., & Pan, Y.
- Affiliations
- Zhejiang University (CN)
- Shanghai Jiao Tong University (CN)
- Hong Kong Association of Registered Tour Co-ordinators (CN)
- Tsinghua University (CN)
- ByteDance (China) (CN)
- Nanjing University (CN)
- Hong Kong University of Science and Technology (HK)
- Meituan (China) (CN)
- Zhejiang Lab (CN)
- Corresponding author
- Pan, Yunhe
- ORCID
- Venue
- Nature Machine Intelligence
- Published
- 2020-06-16
- Volume
- 2
- Issue
- 6
- Pages
- 312-316
- ISSN
- 2522-5839 (ISSN-L)
- OpenAlex
- W3035639004
- Cited by
- 287
- References
- 24
- Citations by year
- 2026: 41 · 2025: 78 · 2024: 70 · 2023: 38 · 2022: 31 · 2021: 26 · 2020: 3
- FWCI
- 9.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Machine Intelligence (publishedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Decision Sciences › Information Systems and Management › Research, Science, and Academia
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- AI policy, basic research, AI ethics, artificial intelligence in education, AI ecosystem, industrial transformation, AI innovation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
