Artificial intelligence-based segmentation of residual pancreatic cancer in resection specimens following neoadjuvant treatment (ISGPP-2)

Author(s):: Janssen, B.V.; Oteman, B.; Ali, M.; Valkema, P.A. (0000-0001-7189-4441); Adsay, V.; Basturk, O.; Chatterjee, D.; Chou, A.; Crobach, S.; Doukas, M.; Drillenburg, P.; Esposito, I.; Gill, A.J.; Hong, S.M.; Jansen, C.; Kliffen, M.; Mittal, A.; Samra, J.; Velthuysen, M.L.F. van; Yavas, A.; Kazemier, G.; Verheij, J.; Steyerberg, E.; Besselink, M.G.; Wang, H.M.; Verbeke, C.; Fariña, A.; Boer, O.J. de; Int Study Grp Pancreatic Pathologists ISGPP; Pancreatobiliary and Hepatic Artificial Intelligence Research PHAIR

pancreatic cancerhistopathologytumor response scoringneoadjuvant therapyartificial intelligencemachine learning

Date issued: 2024-09-30
Language: English
Is part of: The American Journal of Surgical Pathology (2024), Vol. 48, no. 9, p. 1108-1116
hdl: 1887/4214972
doi: 10.1097/PAS.0000000000002270
URL: https://journals.lww.com/ajsp/fulltext/2024/09000/artificial_intelligence_based_segmentation_of.5.aspx