Explainable artificial intelligence in pathology

Author:

Klauschen Frederick,Dippel Jonas,Keyl Philipp,Jurmeister Philipp,Bockmayr Michael,Mock Andreas,Buchstab Oliver,Alber Maximilian,Ruff Lukas,Montavon Grégoire,Müller Klaus-Robert

Publisher

Springer Science and Business Media LLC

Subject

Pathology and Forensic Medicine

Reference50 articles.

1. Klauschen F, Dippel J, Keyl P et al (2024) Toward explainable artificial intelligence for precision pathology. Annu Rev Pathol Mech Dis 19:541–570

2. Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Bartlett PL, Pereira FCN, Burges CJC, Bottou L, Weinberger KQ (Hrsg) Advances in Neural Information Processing Systems 25, S 1106–1114

3. Ronneberger O, Fischer P, Brox T (2015) U‑net: Convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5–9, 2015, Proceedings, Part III 18. Springer, S 234–241

4. Ren S, Kaiming H, Ross B et al (2017) Faster R‑CNN: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137–1149

5. Brown TB, Mann B, Ryder N et al (2020) Language models are few-shot learners. In: NeurIPS

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