Prediction of the mean transit time using machine learning models based on radiomics features from digital subtraction angiography in moyamoya disease or moyamoya syndrome—a development and validation model study
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| Published in | Cardiovascular diagnosis and therapy Vol. 13; no. 5; pp. 879 - 892 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
AME Publishing Company
31.10.2023
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| Subjects | |
| Online Access | Get full text |
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| Author | Peng, Chao Qin, Kun Chen, Guangzhong Gan, Wu Guo, Zhige Zhou, Dong |
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| Author_xml | – sequence: 1 givenname: Kun surname: Qin fullname: Qin, Kun – sequence: 2 givenname: Zhige surname: Guo fullname: Guo, Zhige – sequence: 3 givenname: Chao surname: Peng fullname: Peng, Chao – sequence: 4 givenname: Wu surname: Gan fullname: Gan, Wu – sequence: 5 givenname: Dong surname: Zhou fullname: Zhou, Dong – sequence: 6 givenname: Guangzhong surname: Chen fullname: Chen, Guangzhong |
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| Copyright | 2023 Cardiovascular Diagnosis and Therapy. All rights reserved. 2023 Cardiovascular Diagnosis and Therapy. |
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| DOI | 10.21037/cdt-23-151 |
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| Notes | These authors contributed equally to this work. Contributions: (I) Conception and design: K Qin, G Chen; (II) Administrative support: C Peng, W Gan, Z Guo; (III) Provision of study materials or patients: D Zhou, Z Guo; (IV) Collection and assembly of data: K Qin, C Peng; (V) Data analysis and interpretation: K Qin, Z Guo; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. |
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| Title | Prediction of the mean transit time using machine learning models based on radiomics features from digital subtraction angiography in moyamoya disease or moyamoya syndrome—a development and validation model study |
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