A radiomics feature-based machine learning models to detect brainstem infarction (RMEBI) may enable early diagnosis in non-contrast enhanced CT-Reference-Cited by-同舟云学术

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A radiomics feature-based machine learning models to detect brainstem infarction (RMEBI) may enable early diagnosis in non-contrast enhanced CT

Published:2022-09-28 Issue:2 Volume:33 Page:1004-1014
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Zhang Haiyan,Chen Hongyi,Zhang Chao,Cao Aihong,Lu Qingqing,Wu Hao,Zhang Jun,Geng Daoying

Funder

National Key R&D Program of China

Shanghai Municipal Commission of Science and Technology

Greater Bay Area Institute of Precision Medicine

Industrial Technology Research Institute Medical-Industrial Integration Project

Clinical Research Plan of SHDC

Jiangsu Commission of Health

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-022-09130-6.pdf

Reference33 articles.

1. Ortiz de Mendivil A, Alcalá-Galiano A, Ochoa M, Salvador E, Millán JM (2013) Brainstem stroke: anatomy, clinical and radiological findings. Semin Ultrasound CT MR 34(2):131–141

2. Baran G, Gultekin TO, Baran O et al (2018) Association between etiology and lesion site in ischemic brainstem infarcts: a retrospective observational study. Neuropsychiatr Dis Treat 14:757–766

3. Chalela JA, Kidwell CS, Nentwich LM et al (2007) Magnetic resonance imaging and computed tomography in emergency assessment of patients with suspected acute stroke: a prospective comparison. Lancet 369(9558):293–298

4. Goyal MS, Hoff BG, Williams J et al (2016) Streamlined hyperacute magnetic resonance imaging protocol identifies tissue-type plasminogen activator-eligible stroke patients when clinical impression is stroke mimic. Stroke 47(4):1012–1017

5. Lambin P, Rios-Velazquez E, Leijenaar R et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48(4):441–446

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3. How Can Radiomics Help the Clinical Management of Patients with Acute Ischemic Stroke?;Applied Sciences;2023-09-06

4. Non-contrast CT radiomics and machine learning for outcomes prediction of patients with acute ischemic stroke receiving conventional treatment;European Journal of Radiology;2023-08

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