Early cancer diagnosis via interpretable two-layer machine learning of plasma extracellular vesicle long RNA

doi:10.4251/wjgo.v17.i11.111670

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 17, Issue 11

This Article

(49)

(75)

(0)

(10)

(1)

(715)

(1)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Supplementary Materials of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastrointestinal Oncology

ISSN

1948-5204

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Basic Study

World J Gastrointest Oncol. Nov 15, 2025; 17(11): 111670
Published online Nov 15, 2025. doi: 10.4251/wjgo.v17.i11.111670

Full Size Figure Download Figure

Figure 11 Analysis of overall survival and disease free survival. TPM: Transcripts per kilobase of exon model per million mapped reads; HR: Hazard ratio.

Citation: Liu SC, Zhang H. Early cancer diagnosis via interpretable two-layer machine learning of plasma extracellular vesicle long RNA. World J Gastrointest Oncol 2025; 17(11): 111670
URL: https://www.wjgnet.com/1948-5204/full/v17/i11/111670.htm
DOI: https://dx.doi.org/10.4251/wjgo.v17.i11.111670

Liu SC, Zhang H. Early cancer diagnosis via interpretable two-layer machine learning of plasma extracellular vesicle long RNA. World J Gastrointest Oncol 2025; 17(11): 111670 [PMID: 41281480 DOI: 10.4251/wjgo.v17.i11.111670]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.