Use of Machine Learning to Determine Predictors of Intracerebral Hemorrhage Expansion

被引:0
作者
Azher, Aidan, I
Coronado, Ivan
Savitz, Sean, I
Aronowski, Jaroslaw A.
Salazar-Marioni, Sergio
Abdelkhaleq, Rania
Abdulrazzak, Mohammad Ammar
Greco, Jonathan
Sheth, Sunil
Giancardo, Luca
机构
[1] UTHealth, McGovern Sch Med, Neurol, Houston, TX USA
[2] UTHEALTH, Stroke Inst, Houston, TX USA
[3] Univ Texas Hsc Houston, Houston, TX USA
[4] Univ Texas Houston, Houston, TX USA
[5] Univ Texas Hlth Sci Ctr Houston, Houston, TX 77030 USA
[6] UTHealth, Houston, TX USA
关键词
Machine Learning; Artificial Intelligence; Intracranial hemorrhage; Imaging agents;
D O I
10.1161/str.52.suppl_1.P427
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
AP427
引用
收藏
页数:2
相关论文
共 50 条
  • [11] Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis
    Liu, Yihua
    Zhao, Fengfeng
    Niu, Enjing
    Chen, Liang
    NEURORADIOLOGY, 2024, 66 (09) : 1603 - 1616
  • [12] A Comparative Study of a Nomogram and Machine Learning Models in Predicting Early Hematoma Expansion in Hypertensive Intracerebral Hemorrhage
    Ye, Haoyi
    Jiang, Yang
    Wu, Zhihua
    Ruan, Yaoqin
    Shen, Chen
    Xu, Jiexiong
    Han, Wen
    Jiang, Ruixin
    Cai, Jinhui
    Liu, Zhifeng
    ACADEMIC RADIOLOGY, 2024, 31 (12) : 5130 - 5140
  • [13] Machine learning models predict coagulopathy in spontaneous intracerebral hemorrhage patients in ER
    Zhu, Fengping
    Pan, Zhiguang
    Tang, Ying
    Fu, Pengfei
    Cheng, Sijie
    Hou, Wenzhong
    Zhang, Qi
    Huang, Hong
    Sun, Yirui
    CNS NEUROSCIENCE & THERAPEUTICS, 2021, 27 (01) : 92 - 100
  • [14] Prognostic prediction of hypertensive intracerebral hemorrhage using CT radiomics and machine learning
    Xu, Xinghua
    Zhang, Jiashu
    Yang, Kai
    Wang, Qun
    Chen, Xiaolei
    Xu, Bainan
    BRAIN AND BEHAVIOR, 2021, 11 (05):
  • [15] Prediction of Early Perihematomal Edema Expansion Based on Noncontrast Computed Tomography Radiomics and Machine Learning in Intracerebral Hemorrhage
    Li, Yu-Lun
    Chen, Chu
    Zhang, Li-Juan
    Zheng, Yi-Neng
    Lv, Xin-Ni
    Zhao, Li-Bo
    Li, Qi
    Lv, Fa-Jin
    WORLD NEUROSURGERY, 2023, 175 : E264 - E270
  • [16] Predicting Early Seizures After Intracerebral Hemorrhage with Machine Learning
    Bunney, Gabrielle
    Murphy, Julianne
    Colton, Katharine
    Wang, Hanyin
    Shin, Hye Jung
    Faigle, Roland
    Naidech, Andrew M.
    NEUROCRITICAL CARE, 2022, 37 (SUPPL 2) : 322 - 327
  • [17] Predicting Early Seizures After Intracerebral Hemorrhage with Machine Learning
    Gabrielle Bunney
    Julianne Murphy
    Katharine Colton
    Hanyin Wang
    Hye Jung Shin
    Roland Faigle
    Andrew M. Naidech
    Neurocritical Care, 2022, 37 : 322 - 327
  • [18] Predicting the recurrence of spontaneous intracerebral hemorrhage using a machine learning model
    Cui, Chaohua
    Lan, Jiaona
    Lao, Zhenxian
    Xia, Tianyu
    Long, Tonghua
    FRONTIERS IN NEUROLOGY, 2024, 15
  • [19] Machine learning model to predict sepsis in ICU patients with intracerebral hemorrhage
    Lei Tang
    Ye Li
    Ji Zhang
    Feng Zhang
    Qiaoling Tang
    Xiangbin Zhang
    Sai Wang
    Yupeng Zhang
    Siyuan Ma
    Ran Liu
    Lei Chen
    Junyi Ma
    Xuelun Zou
    Tianxing Yao
    Rongmei Tang
    Huifang Zhou
    Lianxu Wu
    Yexiang Yi
    Yi Zeng
    Duolao Wang
    Le Zhang
    Scientific Reports, 15 (1)
  • [20] Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning
    Garg, Ravi
    Prabhakaran, Shyam
    Holl, Jane L.
    Luo, Yuan
    Faigle, Roland
    Kording, Konrad
    Naidech, Andrew M.
    JOURNAL OF STROKE & CEREBROVASCULAR DISEASES, 2018, 27 (12) : 3570 - 3574