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[Nature] A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics

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期刊：Nature Cancer

文献作者：Danh-Tai Hoang; Gal Dinstag; Eldad D. Shulman; Leandro C. Hermida; Doreen S. Ben-Zvi; Efrat Elis; Katherine Caley; Stephen-John Sammut; Sanju Sinha; Neelam Sinha; Christopher H. Dampier; Chani Stossel; Tejas Patil; Arun Rajan; Wiem Lassoued; Julius Strauss; Shania Bailey; Clint Allen; Jason Redman; Tuvik Beker; Peng Jiang; Talia Golan; Scott Wilkinson; Adam G. Sowalsky; Sharon R. Pine; Carlos Caldas; James L. Gulley; Kenneth Aldape; Ranit Aharonov; Eric A. Stone; Eytan Ruppin

出版日期：--

DOI号：10.1038/s43018-024-00793-2

下载链接：https://www.nature.com/articles/s43018-024-00793-2.pdf

文献链接：https://doi.org/10.1038/s43018-024-00793-2

当前文献来源于 Springer Science and Business Media LLC。

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[Nature] A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics