Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.

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Bibliographic Details
Title: Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.
Authors: Liu C; Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Xueyuan Road 37, Beijing 100191, China., Wang J; Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, South Fourth Ring West Road 119, Beijing 100050, China., Shen J; Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Xueyuan Road 37, Beijing 100191, China., Chen X; Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Xueyuan Road 37, Beijing 100191, China.; School of Engineering Medicine, Beihang University, Xueyuan Road 37, Beijing 100191, China., Ji N; Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, South Fourth Ring West Road 119, Beijing 100050, China., Yue S; Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Xueyuan Road 37, Beijing 100191, China.
Source: PNAS nexus [PNAS Nexus] 2024 May 27; Vol. 3 (6), pp. pgae208. Date of Electronic Publication: 2024 May 27 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press on behalf of the National Academy of Sciences Country of Publication: England NLM ID: 9918367777906676 Publication Model: eCollection Cited Medium: Internet ISSN: 2752-6542 (Electronic) Linking ISSN: 27526542 NLM ISO Abbreviation: PNAS Nexus Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2752-6542
DOI:10.1093/pnasnexus/pgae208