Editorial: Advances in AI methods for computational pathology

Xin Qi; Jun Kong; Fuyong Xing; Guotai Wang; Zhuotun Zhu

doi:10.3389/fmed.2022.974857

Editorial: Advances in AI methods for computational pathology

Front Med (Lausanne). 2022 Sep 21:9:974857. doi: 10.3389/fmed.2022.974857. eCollection 2022.

Authors

Xin Qi¹, Jun Kong², Fuyong Xing³, Guotai Wang⁴, Zhuotun Zhu⁵

Affiliations

¹ Eisai, Nutley, NJ, United States.
² Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, United States.
³ Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, CO, United States.
⁴ School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China.
⁵ Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, United States.

No abstract available

Keywords: artificial intelligence; computational pathology; convolutional neural networks; deep learning; multi-modality; whole-slide image analysis.

Publication types

Editorial