2 citations · 4 across the 7 of their papers we have counts for
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Forget-MI: Machine Unlearning for Forgetting Multimodal Information in Healthcare Settings
Shahad Hardan, Darya Taratynova, Abdelmajid Essofi +2
Privacy preservation in AI is crucial, especially in healthcare, where models rely on sensitive patient data. In the emerging field of machine unlearning, existing methodologies st…
SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network
Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani +2
Survival analysis plays a crucial role in estimating the likelihood of future events for patients by modeling time-to-event data, particularly in healthcare settings where predicti…
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…
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…