Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer

• Main Authors: Tay, T.K.Y, Thike, A.A, Pathmanathan, N, Jara-Lazaro, A.R, Iqbal, J, Sng, A.S.H, Ye, H.S, Lim, J.C.T, Koh, V.C.Y, Tan, J.S.Y, Yeong, J.P.S, Chow, Z.L, Li, H.H, Cheng, C.L, Tan, P.H
• Other Authors: DUKE-NUS MEDICAL SCHOOL
• Format: Article
• Published: 2020
• Subjects: Ki 67 antigen; adult; aged; algorithm; Article; breast cancer; cancer prognosis; cancer recurrence; cancer survival; clinical outcome; computer analysis; computer assisted image analysis; controlled study; differential diagnosis; estrogen receptor positive breast cancer; female; human; human cell; human tissue; image analysis; luminal A breast cancer; luminal B breast cancer; major clinical study; middle aged; overall survival; prediction; scoring system; tissue microarray; tumor invasion; very elderly; young adult
• Online Access: https://scholarbank.nus.edu.sg/handle/10635/178105
• Institution: National University of Singapore

10.18632/oncotarget.24398