A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplace.

"Declarations Ethics approval and consent to participateThis study was approved by the institutional review board of Seegene Medical Foundation and the Institutional Review Board (KAIST-IRB-22-334, KH2020-116) of the Korea Advanced Institute of Science and Technology, the university that collaborated with the medical foundation. Consent for publicationNot applicable. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."

"Funding This research was supported by the Seegene Medical Foundation, South Korea, under the project “Research on Developing a Next Generation Medical Diagnosis System Using Deep Learning” (Grant Number: G01180115). Funding body had no role in the design of the study, analysis and interpretation of data, and in writing the manuscript. but contributed to the collection of data."