A Radiomics Model Based on CT Images Combined with Multiple Machine Learning Models to Predict the Prognosis of Spontaneous Intracerebral Hemorrhage
Author:
Publisher
Elsevier BV
Subject
Neurology (clinical),Surgery
Reference28 articles.
1. A clinical-radiomics nomogram may provide a personalized 90-day functional outcome assessment for spontaneous intracerebral hemorrhage;Song;Eur Radiol,2021
2. Radiomics for intracerebral hemorrhage: are all small hematomas benign?;Zhan;Br J Radiol,2021
3. The added value of intraventricular hemorrhage on the radiomics analysis for the prediction of hematoma expansion of spontaneous intracerebral hemorrhage;Wu;Diagnostics (Basel),2022
4. Combination of hematoma volume and perihematoma radiomics analysis on baseline CT scan predicts the growth of perihematomal edema;Wang;Clin Neuroradiol,2023
5. A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage;Chen;Eur Radiol,2023
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Prognostic value of CT scan-based radiomics in intracerebral hemorrhage patients: A systematic review and meta-analysis;European Journal of Radiology;2024-09
2. Development and validation of a machine learning-based predictive model for assessing the 90-day prognostic outcome of patients with spontaneous intracerebral hemorrhage;Journal of Translational Medicine;2024-03-04
3. Application of Radiomics in Intracerebral Hemorrhage;Advances in Clinical Medicine;2024
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