Publisher
Springer Science and Business Media LLC
Subject
Urology,Computer Science (miscellaneous),Computer Networks and Communications,Computer Science Applications,Computational Mathematics,Biochemistry, Genetics and Molecular Biology (miscellaneous)
Reference113 articles.
1. Abeyagunasekera SHP, Perera Y, Chamara K, Kaushalya U, Sumathipala P, Senaweera O (2022) LISA: Enhance the explainability of medical images unifying current XAI techniques. In Proceedings of the 2022 IEEE 7th International Conference for Convergence in Technology (I2CT), Mumbai, India, 7–9 April 2022; pp. 1–9
2. Abir WH, Uddin MF, Khanam FR, Tazin T, Khan MM, Masud M, Aljahdali S (2022) Explainable AI in diagnosing and anticipating leukemia using transfer learning method. Comput Intell Neurosci. https://doi.org/10.1155/2022/5140148
3. Adadi A, Berrada M (2018) Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access 6:52138–52160
4. Alsinglawi B, Alshari O, Alorjani M, Mubin O, Alnajjar F, Novoa M, Darwish O (2022) An explainable machine learning framework for lung cancer hospital length of stay prediction. Sci Rep 12:607
5. Ancona M, Ceolini E, Öztireli C, Gross M (2017) “Towards better understanding of gradient-based attribution methods for deep neural networks.” arXiv preprint arXiv:1711.06104