March 11, 2024, 4:42 a.m. | Zhengrui Guo, Jiabo Ma, Yingxue Xu, Yihui Wang, Liansheng Wang, Hao Chen

cs.LG updates on arXiv.org arxiv.org

arXiv:2403.05396v1 Announce Type: cross
Abstract: Histopathology serves as the gold standard in cancer diagnosis, with clinical reports being vital in interpreting and understanding this process, guiding cancer treatment and patient care. The automation of histopathology report generation with deep learning stands to significantly enhance clinical efficiency and lessen the labor-intensive, time-consuming burden on pathologists in report writing. In pursuit of this advancement, we introduce HistGen, a multiple instance learning-empowered framework for histopathology report generation together with the first benchmark dataset …

arxiv context cs.ai cs.cl cs.cv cs.lg encoding feature global modal report type via

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Global Data Architect, AVP - State Street Global Advisors

@ State Street | Boston, Massachusetts

Data Engineer

@ NTT DATA | Pune, MH, IN