Tensor factorization toward precision medicine

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Natural Language Processing for EHR-Based Computational Phenotyping (2018, methodology): “[46], they applied tensor factorization [47, 48] on medication orders to generate phenotypes without supervision.”
Multimodal machine learning in precision health: A scoping review (2022, background): “The clinical area of heart failure with preserved ejection fraction (HFpEF) saw novel applications of multiple tensor factorization formulations to integrate the deep phenotypic and trans-omic information 24 , and this extends to other areas of precision medicine 25 .”
Mining Electronic Health Records: A Survey (2017, background): “…2014; Yadav et al. 2015b; Gatti et al. 2011; Sandri et al. 2014; Vinzamuri and Reddy 2013; Peelen et al. 2010; Choi et al. 2015; Wang et al. 2013a; Luo et al. 2016; Hripcsak et al. 2015; Hagar et al. 2014 [Sathyanarayana et al. 2014; White et al. 2013; Iyer et al. 2014; Haerian et al. 2012;…”
Tensor Factorization for Precision Medicine in Heart Failure with Preserved Ejection Fraction (2017, unknown): “We refer the reader to general reviews [40, 41] for tensor modeling application in”