Clinical Applications of Data-enabled Intelligence in Neurology

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ORIGINAL RESEARCH

Published on 07 Jan 2025

Prediction of clinical efficacy of acupuncture intervention on upper limb dysfunction after ischemic stroke based on machine learning: a study driven by DSA diagnostic reports data

Yaning Liu
Yuqi Tang
Zechen Li
Pei Yu
Jing Yuan
Lichuan Zeng
Can Wang
Su Li
Ling Zhao

doi 10.3389/fneur.2024.1441886

ORIGINAL RESEARCH

Published on 04 Dec 2024

Application of digital tools and artificial intelligence in the Myasthenia Gravis Core Examination

Marc Garbey
Quentin Lesport
Helen Girma
Gülşen Öztosun
Mohammed Abu-Rub
Amanda C. Guidon
Vern Juel
Richard J. Nowak
Betty Soliven
1 more
Henry J. Kaminski

doi 10.3389/fneur.2024.1474884

480 views

ORIGINAL RESEARCH

Published on 09 May 2024

Machine learning models reveal the critical role of nighttime systolic blood pressure in predicting functional outcome for acute ischemic stroke after endovascular thrombectomy

Dingkang Xu
Peng Qi
Peng Liu
Hongchun Yang
Gengfan Ye
Dezhi Shan
Shixiong Lei
Guozheng Yang
Junqing Ding
3 more
Jun Lu

doi 10.3389/fneur.2024.1405668

708 views

ORIGINAL RESEARCH

Published on 29 Apr 2024

An exploration on the machine-learning-based stroke prediction model

Shenshen Zhi
Xiefei Hu
Yan Ding
Huajian Chen
Xun Li
Yang Tao
Wei Li

doi 10.3389/fneur.2024.1372431

1,402 views
1 citation

ORIGINAL RESEARCH

Published on 24 Apr 2024

Research on the pathogenesis of Alzheimer's disease based on thalamocortical computational model

Yijin Gang
Tao Li
Xianjing Xu
Qi Zheng
Weiping Wang

doi 10.3389/fneur.2024.1353305

491 views

SYSTEMATIC REVIEW

Published on 02 Apr 2024

Global research trends and hotspots of artificial intelligence research in spinal cord neural injury and restoration—a bibliometrics and visualization analysis

Guangyi Tao
Shun Yang
Junjie Xu
Linzi Wang
Bin Yang

doi 10.3389/fneur.2024.1361235

1,682 views
2 citations

ORIGINAL RESEARCH

Published on 15 Feb 2024

Novel artificial intelligence-based hypodensity detection tool improves clinician identification of hypodensity on non-contrast computed tomography in stroke patients

Angela Dos Santos
Milanka Visser
Longting Lin
Andrew Bivard
Leonid Churilov
Mark William Parsons

doi 10.3389/fneur.2024.1359775

722 views

ORIGINAL RESEARCH

Published on 02 Feb 2024

Machine learning-based prediction of mild cognitive impairment among individuals with normal cognitive function

Xia Wei Zhu
Si Bo Liu
Chen Hua Ji
Jin Jie Liu
Chao Huang

doi 10.3389/fneur.2024.1352423

1,736 views
2 citations

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Artificial Intelligence in Neurology

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Articles

Prediction of clinical efficacy of acupuncture intervention on upper limb dysfunction after ischemic stroke based on machine learning: a study driven by DSA diagnostic reports data

Application of digital tools and artificial intelligence in the Myasthenia Gravis Core Examination

Machine learning models reveal the critical role of nighttime systolic blood pressure in predicting functional outcome for acute ischemic stroke after endovascular thrombectomy

An exploration on the machine-learning-based stroke prediction model

Research on the pathogenesis of Alzheimer's disease based on thalamocortical computational model

Global research trends and hotspots of artificial intelligence research in spinal cord neural injury and restoration—a bibliometrics and visualization analysis

Novel artificial intelligence-based hypodensity detection tool improves clinician identification of hypodensity on non-contrast computed tomography in stroke patients

Machine learning-based prediction of mild cognitive impairment among individuals with normal cognitive function

Frontiers in Neurology

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