Histopathology images predict multi-omics aberrations and prognoses in colorectal can... | RTCL.TV
Channel: STEM RTCL TV
Date: 2023-07-29

### Keywords ###
#multiomicsdata #MOMAplatform #machinelearning #learningapproach #accuratelypredict #survivalrate #clinicalprofiles #RTCLTV #shorts

### Article Attribution ###
Title: Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients
Authors: Pei-Chen Tsai, Tsung-Hua Lee, Kun-Chi Kuo, Fang-Yi Su, Tsung-Lu Michael Lee, Eliana Marostica, Tomotaka Ugai, Melissa Zhao, Mai Chan Lau, Juha P. Väyrynen, Marios Giannakis, Yasutoshi Takashima, Seyed Mousavi Kahaki, Kana Wu, Mingyang Song, Jeffrey A. Meyerhardt, Andrew T. Chan, Jung-Hsien Chiang, Jonathan Nowak, Shuji Ogino ,and Kun-Hsing Yu
Publisher: Nature Portfolio
DOI: 10.1038/s41467-023-37179-4
DOAJ URL: https://doaj.org/article/b1f216841e764eb6bca289a4d9ae84e3
Source URL: https://doi.org/10.1038/s41467-023-37179-4



### Image Attribution ###
We used stable diffusion to programmatically generate the background images. 
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### Video Timestamps ###
0:00:00 - Summary 
0:00:26 - Title 
0:00:32 - End