Whole urine-based multiple cancer diagnosis and metabolite profiling using 3D evolutionary gold nanoarchitecture combined with machine learning-assisted SERS-Reference-Cited by-同舟云学术

Whole urine-based multiple cancer diagnosis and metabolite profiling using 3D evolutionary gold nanoarchitecture combined with machine learning-assisted SERS

Published:2024-08 Issue: Volume:412 Page:135828
ISSN:0925-4005
Container-title:Sensors and Actuators B: Chemical
language:en
Short-container-title:Sensors and Actuators B: Chemical

Author:

Al Ja’farawy Muhammad Shalahuddin,Linh Vo Thi Nhat,Yang Jun-Yeong,Mun Chaewon,Lee Seunghun,Park Sung-Gyu,Han In Woong,Choi Samjin,Lee Min-Young,Kim Dong-Ho,Jung Ho Sang

Funder

Korea Institute of Materials Science

National Research Foundation of Korea

Publisher

Elsevier BV

Reference55 articles.

1. Metabolomic fingerprinting for the detection of early-stage lung cancer: from the genome to the metabolome;Haince;Int. J. Mol. Sci.,2022

2. A simple paper-based surface enhanced Raman scattering (SERS) platform and magnetic separation for cancer screening;Reokrungruang;Sens. Actuators B,2019

3. Label-Free SERS analysis of urine using a 3D-stacked AgNW-glass fiber filter sensor for the diagnosis of pancreatic cancer and prostate cancer;Phyo;Anal. Chem.,2021

4. Cancer metabolomic markers in urine: evidence, techniques and recommendations;Dinges;Nat. Rev. Urol.,2019

5. Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry;Silva;Br. J. Cancer,2011

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system;Biosensors and Bioelectronics;2024-11