A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage-Reference-Cited by-同舟云学术

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A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage

Published:2024-06 Issue: Volume: Page:
ISSN:1076-6332
Container-title:Academic Radiology
language:en
Short-container-title:Academic Radiology

Author:

Ye Haoyi,Jiang Yang,Wu Zhihua,Ruan Yaoqin,Shen Chen,Xu Jiexiong,Han Wen,Jiang Ruixin,Cai Jinhui,Liu Zhifeng^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. Defining hematoma expansion in intracerebral hemorrhage: relationship with patient outcomes;Dowlatshahi;Neurology,2011

2. Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review;Feigin;Lancet Neurol,2009

3. Ultra-early hemostatic therapy for intracerebral hemorrhage;Mayer;Stroke,2003

4. Hematoma growth is a determinant of mortality and poor outcome after intracerebral hemorrhage;Davis;Neurology,2006

5. Rapid blood-pressure lowering in patients with acute intracerebral hemorrhage;Anderson;N Engl J Med,2013

Cited by 1 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. A Deep Learning-Based Framework for Predicting Intracerebral Hemorrhage Hematoma Expansion Using Head Non-contrast CT Scan;Academic Radiology;2024-08

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