Publisher
Springer Science and Business Media LLC
Subject
Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition
Reference102 articles.
1. Payrovnaziri SN, Chen Z, Rengifo-Moreno P, Miller T, Bian J, Chen JH, et al. Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review. J Am Med Inform Assoc. 2020;27(7):1173–85.
2. Deeks A. The judicial demand for explainable artificial intelligence. Columbia Law Rev. 2019;119(7):1829–50.
3. Gao X, Gong R, Zhao Y, Wang S, Shu T, Zhu SC. Joint mind modeling for explanation generation in complex human-robot collaborative tasks. In: 2020 29th IEEE international conference on robot and human interactive communication (RO-MAN). IEEE; 2020. p. 1119–26.
4. Cambria E, Liu Q, Decherchi S, Xing F, Kwok K. SenticNet 7: a commonsense-based neurosymbolic AI framework for explainable sentiment analysis. Proceedings of LREC 2022. 2022.
5. Guidotti R, Monreale A, Ruggieri S, Turini F, Giannotti F, Pedreschi D. A survey of methods for explaining black box models. CSUR. 2018;51(5).
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献