Machine learning-based exosome profiling of multi-receptor SERS sensors for differentiating adenocarcinoma in situ from early-stage invasive adenocarcinoma-Reference-Cited by-同舟云学术

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Machine learning-based exosome profiling of multi-receptor SERS sensors for differentiating adenocarcinoma in situ from early-stage invasive adenocarcinoma

Published:2024-04 Issue: Volume:236 Page:113824
ISSN:0927-7765
Container-title:Colloids and Surfaces B: Biointerfaces
language:en
Short-container-title:Colloids and Surfaces B: Biointerfaces

Author:

Lu Dechan,Zhang Bohan,Shangguan Zhikun,Lu Yudong,Chen Jingbo,Huang Zufang

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference30 articles.

1. Non-small-cell lung cancer;Gridelli;Nat. Rev. Dis. Prim.,2015

2. The liquid biopsy for lung cancer: state of the art, limitations and future developments;Di Capua;Cancers,2021

3. Artificial intelligence and lung cancer: impact on improving patient outcomes;Gandhi;Cancers,2023

4. Histological scoring for small lung adenocarcinomas 2 cm or less in diameter: a reliable prognostic indicator;Maeshima;J. Thorac. Oncol.,2010

5. Exosomes: small vesicles with big roles in cancer, vaccine development, and therapeutics;Thakur;Bioact. Mater.,2022

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1. Artificial intelligence-based plasma exosome label-free SERS profiling strategy for early lung cancer detection;Analytical and Bioanalytical Chemistry;2024-07-17

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