Frontiers in Neurology | Artificial Intelligence in Neurology

Original Research

Published on 14 Aug 2026

Machine learning–based prediction of in-hospital deep vein thrombosis in patients with acute ischemic stroke: a multicenter study

in Artificial Intelligence in Neurology

Tieshi Zhu
Runzhui Lin
Le Zhao
He Zhu

Frontiers in Neurology

doi 10.3389/fneur.2026.1847449

261 views

Original Research

Accepted on 13 Aug 2026

Predicting Long-Term Outcomes in Intracerebral Hemorrhage: A Comparative Study of Machine Learning Models Highlights the Prognostic Value of Hematoma Clearance

in Artificial Intelligence in Neurology

Cheng Zhang
Yuchen Jiang
Jiaqi Lin
Shengsheng Ge
Zhonghuai Zhang
Ling Yuan
Hangzhe Sun

Frontiers in Neurology

101 views

Original Research

Published on 11 Aug 2026

Assessing the performance of artificial intelligence in detecting electrographic status epilepticus when human experts often disagree

in Artificial Intelligence in Neurology

Khalid Alsherbini
Michelle Armenta Salas
Suganya Karunakaran
Archit Gupta
Baharan Kamousi
Raymond Woo
Veeresh Kumar N. Shivamurthy
David King-Stephens
Lawrence J. Hirsch
John Stern

Frontiers in Neurology

doi 10.3389/fneur.2026.1833203

352 views

Original Research

Published on 10 Aug 2026

LASSO-based nomogram and machine learning models for predicting 30-day nasogastric tube dependence after acute ischemic stroke

in Artificial Intelligence in Neurology

Qianqian Shang
Yu Lei
Hongguang Chen
Zhongli Liu
Minyue Sun
Shuang Wang
Shiyu Wen
Yingying Deng
Min Luo

Frontiers in Neurology

doi 10.3389/fneur.2026.1811560

383 views

Original Research

Accepted on 07 Aug 2026

Privacy-preserving synthetic data from a national CIDP registry: validation against real-world evidence

in Artificial Intelligence in Neurology

alessio Signori
Erika Schirinzi
Fiore Manganelli
Dario Cocito
Yuri Matteo Falzone
Chiara Briani
Anna Mazzeo
Angelo Schenone
Vincenzo Di Stefano
Giuseppe Cosentino

Frontiers in Neurology

147 views

Original Research

Published on 04 Aug 2026

Boundary-aware and uncertainty-guided deep learning for multimodal magnetic resonance imaging segmentation of stroke lesions

in Artificial Intelligence in Neurology

Zhongxiang Xing
Yuding Luo
Yupeng Niu
Yilin Yang
Zhenzhen Lin
Han Qin
Zhiyin Chen
Jian Wang
Jiong Mu

Frontiers in Neurology

doi 10.3389/fneur.2026.1872532

423 views

Original Research

Published on 03 Aug 2026

Data-centric strategies enable cross-center generalization of convolutional neural networks for CT brain extraction

in Artificial Intelligence in Neurology

Zheng Sun
Lifang Ye
Yao Xu
Yuehua Li

Frontiers in Neurology

doi 10.3389/fneur.2026.1895626

316 views

Original Research

Published on 28 Jul 2026

A single model for glioblastoma segmentation with and without T2-FLAIR: independent validation of a targeted dropout strategy

in Artificial Intelligence in Neurology

Marco Öchsner
Lena Kaiser
Robert Stahl
Nathalie L. Albert
Thomas Liebig
Robert Forbrig
Jonas Reis

Frontiers in Neurology

doi 10.3389/fneur.2026.1889198

368 views

Original Research

Accepted on 27 Jul 2026

CT-Based Intrathrombus and Perithrombus Radiomics for Predicting Complete Recanalization After Endovascular Thrombectomy in Acute Ischemic Stroke

in Artificial Intelligence in Neurology

Qianqian Zhao
Shuaishuai Feng
Huihui Jia
Minda Li
Hao Tian
Haibin Pan
Jingxuan Jiang

Frontiers in Neurology

205 views

Original Research

Published on 24 Jul 2026

Development and external validation of a machine learning model based on multimodal dynamic data for predicting shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage: a dual-center retrospective cohort study

in Artificial Intelligence in Neurology

Chengzhang Zheng
Jianhuang Huang
Xinguo Wang
Qing Ye
Caihou Lin
Xiang Gu

Frontiers in Neurology

doi 10.3389/fneur.2026.1837898

532 views

Original Research

Published on 23 Jul 2026

DBENet: Dual-Branch Encoder Network for brain MRI lesion segmentation

in Artificial Intelligence in Neurology

Qiang Zhao
Zhaohui Zhang
Tinghua Cao

Frontiers in Neurology

doi 10.3389/fneur.2026.1766271

30,677 views

Original Research

Published on 23 Jul 2026

GMANet: a CPU-only ultra-lightweight 3D CNN for real-time glioma triage in resource-limited environments

in Artificial Intelligence in Neurology

Caijian Hua
Xuerong Jing
Liuying Li
Xia Zhou

Frontiers in Neurology

doi 10.3389/fneur.2026.1894796

944 views

Original Research

Published on 20 Jul 2026

EEGDecoder-x: an explainable deep learning framework for cross-subject EEG-based detection of Alzheimer's and Creutzfeldt–Jakob disease

in Artificial Intelligence in Neurology

Muhammad Suffian
Nadia Mammone
Cosimo Ieracitano
Giovanbattista Gaspare Tripodi
Angelo Pascarella
Edoardo Ferlazzo
Francesco Carlo Morabito

Frontiers in Neurology

doi 10.3389/fneur.2026.1851752

619 views

Study Protocol

Published on 17 Jul 2026

AI-based predictive biomarkers for chronic neurological diseases: the rAIdD prospective, multicenter, observational study protocol

in Artificial Intelligence in Neurology

Simone Varrasi
Alfredo Pulvirenti
Vincenzo Catania
Maurizio Palesi
Concetto Spampinato
Davide Patti
Orazio Tomarchio
Giovanni Micale
Alessia Simone
Lisa Passarello

Frontiers in Neurology

doi 10.3389/fneur.2026.1885919

1,063 views

Original Research

Published on 17 Jul 2026

An edge-aware salient context fusion and refinement network for hippocampal segmentation in MR images and its diagnostic value for mild cognitive impairment

in Artificial Intelligence in Neurology

Limin Liu
Xiaolong Chen
Qiqun Zeng
Shili Zhou
Xia Zhang

Frontiers in Neurology

doi 10.3389/fneur.2026.1899123

541 views

Original Research

Published on 16 Jul 2026

Speech-based concussion detection in athletes using Mel-spectrograms and convolutional neural networks

in Artificial Intelligence in Neurology

Rahmina Rubaiat
Christian Poellabauer

Frontiers in Neurology

doi 10.3389/fneur.2026.1830075

879 views

Original Research

Published on 15 Jul 2026

APLG-Net: an anatomy-guided local-global hybrid network with progression-aware supervision for structural MRI-based NC/MCI/AD classification

in Artificial Intelligence in Neurology

Bin Shi
Zhimin Wang
Jing Lian
Zhaorui Yang
Xiaona Zuo

Frontiers in Neurology

doi 10.3389/fneur.2026.1885491

3,279 views

Correction

Published on 15 Jul 2026

Correction: Machine learning-based prediction model for cognitive frailty in elderly patients with ischaemic stroke: a prospective cohort study

in Artificial Intelligence in Neurology

Xuan Chen
Linjie Zhou
Ying Zhang
Tuonan Liu
Bo Yan
Yang Li
Yan Hua

Frontiers in Neurology

doi 10.3389/fneur.2026.1907107

875 views

Original Research

Published on 14 Jul 2026

Development and validation of a nomogram for predicting recurrence in patients with Meige syndrome after radiofrequency ablation

in Artificial Intelligence in Neurology

Xiang Xu
Tao Wang
Zi Wang

Frontiers in Neurology

doi 10.3389/fneur.2026.1841516

559 views

Study Protocol

Published on 10 Jul 2026

Machine and deep learning based on magnetic resonance imaging to segment glioblastoma and predict the spread of recurrence: a multicenter retrospective protocol

in Artificial Intelligence in Neurology

Luana Conte
Erica Lo Turco
Rosaria V. Abbritti
Caterina Accettura
Giuseppe Raso
Edvige Iaboni
Ugo De Giorgi
Giorgio De Nunzio
Donato Cascio
Maria Caffo

Frontiers in Neurology

doi 10.3389/fneur.2026.1818594

2,664 views

Review

Published on 09 Jul 2026

A narrative review of AI monitoring in postoperative pain management and functional rehabilitation for spinal cord injury

in Artificial Intelligence in Neurology

Xiaoqing Zhang
Jianping Sheng

Frontiers in Neurology

doi 10.3389/fneur.2026.1838329

806 views

Original Research

Published on 09 Jul 2026

Latent profile analysis of emergency department presentation characteristics in patients with acute ischemic stroke

in Artificial Intelligence in Neurology

Xiangguang Yin
Hua Xu
Jing Wei
Ying Li
Ying Chen

Frontiers in Neurology

doi 10.3389/fneur.2026.1758671

615 views

Original Research

Published on 06 Jul 2026

Utilizing conditional generative adversarial network to generate head MRA based on nonvascular sequences: comparative study of single-modality and multi-modality methods

in Artificial Intelligence in Neurology

Xinyu Song
Lei Xiang
Ping Wang
Chao Zhu
Zhongzheng Cao
Xiaoer Wei
Tianen Yu
Tao Zhou
Yuehua Li

Frontiers in Neurology

doi 10.3389/fneur.2026.1857271

755 views

Original Research

Published on 06 Jul 2026

A multimodal multi-agent LLM framework for identifying key drivers of sleep disorders

in Artificial Intelligence in Neurology

Chongyang Fu
Syed Kamaruzaman Bin Syed Ali
Mohd Shahril Nizam Bin Shaharom

Frontiers in Neurology

doi 10.3389/fneur.2026.1851192

1,169 views

179 articles

articles

Machine learning–based prediction of in-hospital deep vein thrombosis in patients with acute ischemic stroke: a multicenter study

Predicting Long-Term Outcomes in Intracerebral Hemorrhage: A Comparative Study of Machine Learning Models Highlights the Prognostic Value of Hematoma Clearance

Assessing the performance of artificial intelligence in detecting electrographic status epilepticus when human experts often disagree

LASSO-based nomogram and machine learning models for predicting 30-day nasogastric tube dependence after acute ischemic stroke

Privacy-preserving synthetic data from a national CIDP registry: validation against real-world evidence

Boundary-aware and uncertainty-guided deep learning for multimodal magnetic resonance imaging segmentation of stroke lesions

Data-centric strategies enable cross-center generalization of convolutional neural networks for CT brain extraction

A single model for glioblastoma segmentation with and without T2-FLAIR: independent validation of a targeted dropout strategy

CT-Based Intrathrombus and Perithrombus Radiomics for Predicting Complete Recanalization After Endovascular Thrombectomy in Acute Ischemic Stroke

Development and external validation of a machine learning model based on multimodal dynamic data for predicting shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage: a dual-center retrospective cohort study

DBENet: Dual-Branch Encoder Network for brain MRI lesion segmentation

GMANet: a CPU-only ultra-lightweight 3D CNN for real-time glioma triage in resource-limited environments

EEGDecoder-x: an explainable deep learning framework for cross-subject EEG-based detection of Alzheimer's and Creutzfeldt–Jakob disease

AI-based predictive biomarkers for chronic neurological diseases: the rAIdD prospective, multicenter, observational study protocol

An edge-aware salient context fusion and refinement network for hippocampal segmentation in MR images and its diagnostic value for mild cognitive impairment

Speech-based concussion detection in athletes using Mel-spectrograms and convolutional neural networks

APLG-Net: an anatomy-guided local-global hybrid network with progression-aware supervision for structural MRI-based NC/MCI/AD classification

Correction: Machine learning-based prediction model for cognitive frailty in elderly patients with ischaemic stroke: a prospective cohort study

Development and validation of a nomogram for predicting recurrence in patients with Meige syndrome after radiofrequency ablation

Machine and deep learning based on magnetic resonance imaging to segment glioblastoma and predict the spread of recurrence: a multicenter retrospective protocol

A narrative review of AI monitoring in postoperative pain management and functional rehabilitation for spinal cord injury

Latent profile analysis of emergency department presentation characteristics in patients with acute ischemic stroke

Utilizing conditional generative adversarial network to generate head MRA based on nonvascular sequences: comparative study of single-modality and multi-modality methods

A multimodal multi-agent LLM framework for identifying key drivers of sleep disorders