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Comment
. 2023 Apr;29(4):793-794.
doi: 10.1038/s41591-023-02298-4.

Using AI to improve the molecular classification of brain tumors

No authors listed
Comment

Using AI to improve the molecular classification of brain tumors

No authors listed. Nat Med. 2023 Apr.
No abstract available

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References

    1. Louis, D. N. et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro. Oncol. 21, 1498–1508 (2021). This paper summarizes the updated WHO tumor classification with full integration of molecular features for brain tumor diagnosis.
    1. Stupp, R. et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 352, 987–996 (2005). This paper established the current standard-of-care treatment of glioblastoma. - DOI - PubMed
    1. Orringer, D. A. et al. Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat. Biomed. Eng. 1, 0027 (2017). This paper demonstrates the feasibility of integrating SRH into the clinical workflow for brain tumor diagnosis. - DOI - PubMed - PMC
    1. Hollon, T. C. et al. Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nat. Med. 26, 52–58 (2020). This paper shows that deep neural networks can perform as well as pathologists for histologic brain tumor diagnosis. - DOI - PubMed - PMC
    1. Vaswani, A. et al. Attention is all you need. Adv. Neural Inf. Process. Syst. 30 (2017). This paper introduced the transformer neural network architecture.

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