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
  • [1] Prediction of Hematoma Expansion in Intracerebral Hemorrhage in 24 Hours by Machine Learning Algorithm
    Du, Chaonan
    Li, Yan
    Yang, Mingfei
    Ma, Qingfang
    Ge, Sikai
    Ma, Chiyuan
    WORLD NEUROSURGERY, 2024, 185 : E475 - E483
  • [2] Identifying Modifiable Predictors of Patient Outcomes After Intracerebral Hemorrhage with Machine Learning
    Hall, Andrew N.
    Weaver, Bradley
    Liotta, Eric
    Maas, Matthew B.
    Faigle, Roland
    Mroczek, Daniel K.
    Naidech, Andrew M.
    NEUROCRITICAL CARE, 2021, 34 (01) : 73 - 84
  • [3] A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage
    Chen, Yihao
    Qin, Chenchen
    Chang, Jianbo
    Lyu, Yan
    Zhang, Qinghua
    Ye, Zeju
    Li, Zhaojian
    Tian, Fengxuan
    Ma, Wenbin
    Wei, Junji
    Feng, Ming
    Yao, Jianhua
    Wang, Renzhi
    EUROPEAN RADIOLOGY, 2023, 33 (06) : 4052 - 4062
  • [4] A machine learning approach for predicting perihematomal edema expansion in patients with intracerebral hemorrhage
    Yihao Chen
    Chenchen Qin
    Jianbo Chang
    Yan Lyu
    Qinghua Zhang
    Zeju Ye
    Zhaojian Li
    Fengxuan Tian
    Wenbin Ma
    Junji Wei
    Ming Feng
    Jianhua Yao
    Renzhi Wang
    European Radiology, 2023, 33 : 4052 - 4062
  • [5] Identifying Modifiable Predictors of Patient Outcomes After Intracerebral Hemorrhage with Machine Learning
    Andrew N. Hall
    Bradley Weaver
    Eric Liotta
    Matthew B. Maas
    Roland Faigle
    Daniel K. Mroczek
    Andrew M. Naidech
    Neurocritical Care, 2021, 34 : 73 - 84
  • [6] Computed Tomography Imaging Predictors of Intracerebral Hemorrhage Expansion
    Lv, Xin-Ni
    Deng, Lan
    Yang, Wen-Song
    Wei, Xiao
    Li, Qi
    CURRENT NEUROLOGY AND NEUROSCIENCE REPORTS, 2021, 21 (05)
  • [7] Machine Learning for Onset Prediction of Patients with Intracerebral Hemorrhage
    Rusche, Thilo
    Wasserthal, Jakob
    Breit, Hanns-Christian
    Fischer, Urs
    Guzman, Raphael
    Fiehler, Jens
    Psychogios, Marios-Nikos
    Sporns, Peter B.
    JOURNAL OF CLINICAL MEDICINE, 2023, 12 (07)
  • [8] Initial investigation of predicting hematoma expansion for intracerebral hemorrhage using imaging biomarkers and machine learning
    Swetz, Dennis
    Seymour, Samantha E.
    Rava, Ryan A.
    Bhurwani, Mohammad Mahdi Shiraz
    Monteiro, Andre
    Baig, Ammad A.
    Waqas, Muhammad
    Snyder, Kenneth, V
    Levy, Elad, I
    Davies, Jason M.
    Siddiqui, Adnan H.
    Ionita, Ciprian N.
    MEDICAL IMAGING 2022: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING, 2022, 12036
  • [9] Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion
    Chongfeng Duan
    Fang Liu
    Song Gao
    Jiping Zhao
    Lei Niu
    Nan Li
    Song Liu
    Gang Wang
    Xiaoming Zhou
    Yande Ren
    Wenjian Xu
    Xuejun Liu
    Clinical Neuroradiology, 2022, 32 : 215 - 223
  • [10] Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion
    Duan, Chongfeng
    Liu, Fang
    Gao, Song
    Zhao, Jiping
    Niu, Lei
    Li, Nan
    Liu, Song
    Wang, Gang
    Zhou, Xiaoming
    Ren, Yande
    Xu, Wenjian
    Liu, Xuejun
    CLINICAL NEURORADIOLOGY, 2022, 32 (01) : 215 - 223