A Novel High-Dimensional Kernel Joint Non-Negative Matrix Factorization With Multimodal Information for Lung Cancer Study-Reference-Cited by-同舟云学术

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A Novel High-Dimensional Kernel Joint Non-Negative Matrix Factorization With Multimodal Information for Lung Cancer Study

Published:2024-02 Issue:2 Volume:28 Page:976-987
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Shi Yuhu¹^ORCID,Jin Zhibin¹^ORCID,Deng Jin²^ORCID,Zeng Weiming¹^ORCID,Zhou Lili³^ORCID

Affiliation:

1. Information Engineering College, Shanghai Maritime University, Shanghai, China

2. College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China

3. Yangpu District Central Hospital, Shanghai, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10422840/10336413.pdf?arnumber=10336413

Reference54 articles.

1. The biology and management of non-small cell lung cancer

2. Clinical and Genetic Implications of Mutation Burden in Squamous Cell Carcinoma of the Lung

3. Tumor suppression by miR-26 overrides potential oncogenic activity in intestinal tumorigenesis

4. Transcriptomic and functional network features of lung squamous cell carcinoma through integrative analysis of GEO and TCGA data

5. Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods

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