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AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology

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By Eldad D. Shulman, Emma M Campagnolo, Roshan Lodha, Youngmin Chung, Amos Stemmer, Thomas Cantore, Beibei Ru, Tian-Gen Chang, Sumona Biswas, Saugato Rahman Dhruba, Sumeet Patiyal, Sushant Patkar, Andrew Wang, Ranjan Barman, Chuhan Wang, Rohit Paul, Tom Hu, MacLean P. Nasrallah, Ellis Patrick, Jean Yang, Yuan Yuan, Karine Shahen Sargsyan, Padma Sheila Rajagopal, Stephen-John Sammut, Stanley Lipkowitz, Peng Jiang, Carlos Caldas, Kenneth Aldape, Joo Sang Lee, Danh-Tai Hoang, Eytan Ruppin, Sarath Chandra Kalisetty, Amy Plotkin, Simon R.V. Knott
| Cell Press Verified
Keywords digital pathology artificial intelligence deep learning breast cancer spatial transcriptomics spatial biomarkers histopathology treatment response prediction HER2 tumor microenvironment Get full text access Log in, subscribe or purchase for full access. References 1. Wu, S.Z. ∙ Al-Eryani, G. ∙ Roden, D.L. ... A single-cell and spatially resolved atlas of human breast cancers Nat. Genet. 2021; 53:1334-1347 2. Wang, X. ∙ Wang, Z. ∙ Liao, Q. ...
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