Documentdetail
ID kaart
oai:arXiv.org:2308.09725
Onderwerp
Quantitative Biology - Genomics Computer Science - Artificial Inte... Computer Science - Machine Learnin...Auteur
Yang, Ziwei Chen, Zheng Matsubara, Yasuko Sakurai, YasushiCategorie
Computer Science
Jaar
2023
vermelding datum
30-08-2023
Trefwoorden
omics cancerBeschrijving
Precision medicine fundamentally aims to establish causality between dysregulated biochemical mechanisms and cancer subtypes.
Omics-based cancer subtyping has emerged as a revolutionary approach, as different level of omics records the biochemical products of multistep processes in cancers.
This paper focuses on fully exploiting the potential of multi-omics data to improve cancer subtyping outcomes, and hence developed MoCLIM, a representation learning framework.
MoCLIM independently extracts the informative features from distinct omics modalities.
Using a unified representation informed by contrastive learning of different omics modalities, we can well-cluster the subtypes, given cancer, into a lower latent space.
This contrast can be interpreted as a projection of inter-omics inference observed in biological networks.
Experimental results on six cancer datasets demonstrate that our approach significantly improves data fit and subtyping performance in fewer high-dimensional cancer instances.
Moreover, our framework incorporates various medical evaluations as the final component, providing high interpretability in medical analysis.
;Comment: CIKM'23 Long/Full Papers
Yang, Ziwei,Chen, Zheng,Matsubara, Yasuko,Sakurai, Yasushi, 2023, MoCLIM: Towards Accurate Cancer Subtyping via Multi-Omics Contrastive Learning with Omics-Inference Modeling
Choice Between Partial Trajectories: Disentangling Goals from Beliefs
agents models aligned based bootstrapped learning reward function model return choice choices partial
Adverse and serious adverse events incidence of pharmacological interventions for managing chronic and episodic migraine in adults: a systematic review
aes medications bta incidence migraine drugs disorders
