11 citations · 25 across the 14 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2022★ 1 cited
Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer Data
Sayed Hashim, Karthik Nandakumar, Mohammad Yaqub
We have gained access to vast amounts of multi-omics data thanks to Next Generation Sequencing. However, it is challenging to analyse this data due to its high dimensionality and m…
cs.LG2022
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
Sayed Hashim, Muhammad Ali, Karthik Nandakumar +1
For personalized medicines, very crucial intrinsic information is present in high dimensional omics data which is difficult to capture due to the large number of molecular features…