A correspondence of evaluation of deep learning algorithms in detecting Moyamoya disease: a systematic review and single-arm meta-analysis-Reference-Cited by-同舟云学术

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A correspondence of evaluation of deep learning algorithms in detecting Moyamoya disease: a systematic review and single-arm meta-analysis

Published:2024-08-21 Issue:1 Volume:47 Page:
ISSN:1437-2320
Container-title:Neurosurgical Review
language:en
Short-container-title:Neurosurg Rev

Author:

Li Xiaojian,Chen Shiyu,Chen Shupeng,Qiu Guirong

Funder

Jiangxi Province College Students Innovation and Entrepreneurship Training Program

Technology Innovation Team of Jiangxi University of Traditional Chinese Medicine

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10143-024-02701-9.pdf

Reference5 articles.

1. Santana LS, Leite M, Yoshikawa MH et al (2024) Evaluation of deep learning algorithms in detecting moyamoya disease: a systematic review and single-arm meta-analysis. Neurosurg Rev. ;47(1):300. https://doi.org/10.1007/s10143-024-02537-3. PMID: 38951288

2. Esteva A, Robicquet A, Ramsundar B et al (2019) A guide to deep learning in healthcare. Nat Med 25(1):24–29. https://doi.org/10.1038/s41591-018-0316-zEpub 2019 Jan 7. PMID: 30617335

3. Hu Z, Tian W, Guo J et al (2020) Mapping research collaborations in different countries and regions: 1980–2019. Scientometrics 124:729–745. https://doi.org/10.1007/s11192-020-03484-8

4. Vohra V, Watley DC, Yan CH et al (2022) Predictors of academic career placement and scholarly impact in fellowship-trained rhinologists. Int Forum Allergy Rhinol. ;12(1):62–70. https://doi.org/10.1002/alr.22873. Epub 2021 Jul 26. PMID: 34309228

5. Zhang Y, Liu X, Qiao X et al (2023) Characteristics and emerging trends in Research on Rehabilitation Robots from 2001 to 2020: Bibliometric Study. J Med Internet Res 25:e42901. https://doi.org/10.2196/42901PMID: 37256670; PMCID: PMC10267796

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