Obtaining spatially resolved tumor purity maps using deep multiple instance learning in a pan-cancer study

Obtaining spatially resolved tumor purity maps using deep multiple instance learning in a pan-cancer study

10.1016/j.patter.2021.100399

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Bibliographic Details
Main Authors:	Oner, MU, Chen, J, Revkov, E, James, A, Heng, SY, Kaya, AN, Alvarez, JJS, Takano, A, Cheng, XM, Lim, TKH, Tan, DSW, Zhai, W, Skanderup, AJ, Sung, WK, Lee, HK
Other Authors:	BIOLOGICAL SCIENCES
Format:	Article
Published:	Elsevier BV 2022
Subjects:	computational pathology deep learning digital histopathology digital pathology genomic sequencing multiple instance learning spatial omics tumor microenvironment tumor purity whole-slide images
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/226614
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Institution:	National University of Singapore

Description
Summary:	10.1016/j.patter.2021.100399