Frontiers in Neurology | Artificial Intelligence in Neurology

Brief Research Report

Published on 13 Feb 2026

Construction and evaluation of a diagnostic prediction model for bacterial meningitis based on clinical and laboratory data

in Artificial Intelligence in Neurology

Xiaotong Shen
Lidan Xing
Shichao Gao
Yaomeng Huang
Xinhui Yu
Zheng Zhang

Frontiers in Neurology

doi 10.3389/fneur.2026.1747753

248 views

Original Research

Published on 13 Feb 2026

Interpretable machine learning for predicting 30-day mortality following intracranial hemorrhage surgery

in Artificial Intelligence in Neurology

Ziyang Wang
Wenbin Chen
Yan Shi

Frontiers in Neurology

doi 10.3389/fneur.2026.1716346

232 views

Editorial

Accepted on 12 Feb 2026

Editorial: Technology Developments and Clinical Applications of Artificial Intelligence in Neurodegenerative Diseases

in Artificial Intelligence in Neurology

Chang Li
Chuanming Li

Frontiers in Neurology

Mini Review

Accepted on 10 Feb 2026

Convolutional Neural Networks: Applications, Challenges and Future Prospects in Brain Tumor Research

in Artificial Intelligence in Neurology

Peng Zhang
Zhen Yang

Frontiers in Neurology

163 views

Brief Research Report

Accepted on 06 Feb 2026

Causal Dynamic Decision-Making for Robotic Systems in Non-Markovian High-Difficulty Surgery

in Artificial Intelligence in Neurology

Na Guo
Minghui Tan
Tiantian Li
Yang Liu
Qinjian Zhang
Yuanxin Li
Tianlei Xu
Fuchun Sun

Frontiers in Neurology

110 views

Original Research

Accepted on 06 Feb 2026

DenseLes: Slice-Wise Dense Network for Multiple Sclerosis Lesion Segmentation and Classication

in Artificial Intelligence in Neurology

Melinda Katona
Bence Bozsik
Péter Bodnár
Krisztián Kocsis
Eszter Tóth
Nikoletta Szabó
András Király
Péter Faragó
László G. Nyúl
Dániel Veréb

Frontiers in Neurology

229 views

Original Research

Published on 06 Feb 2026

Automatic and standardized reporting of perioperative MRIs in patients with central nervous system tumors

in Artificial Intelligence in Neurology

David Bouget
Mathilde Gajda Faanes
Asgeir Store Jakola
Frederik Barkhof
Hilko Ardon
Lorenzo Bello
Mitchel S. Berger
Shawn L. Hervey-Jumper
Julia Furtner
Albert J. S. Idema

Frontiers in Neurology

doi 10.3389/fneur.2025.1707481

533 views

Original Research

Published on 04 Feb 2026

Machine learning models for predicting extended length of stay and hospital charges in nontraumatic subarachnoid hemorrhage

in Artificial Intelligence in Neurology

Di Wu
Sihan Wang
Cong Wang
Yijia Xiang
Lingyu Hao
Zhen Wang
Xingye Zhai
Yi Wang

Frontiers in Neurology

doi 10.3389/fneur.2026.1737503

550 views

Review

Accepted on 03 Feb 2026

Deep learning and high-resolution magnetic resonance vascular wall imaging: current challenges and future perspectives

in Artificial Intelligence in Neurology

Zhiming Cui
Huiqing Zhang
JI BO HU

Frontiers in Neurology

Mini Review

Accepted on 02 Feb 2026

Artificial Intelligence-Driven Clinical Auxiliary Diagnosis of Benign Paroxysmal Positional Vertigo

in Artificial Intelligence in Neurology

Siyang Dai
Ying Wu
Xiaocui Kang
Zuoting Shen
Zhong Ping

Frontiers in Neurology

129 views

Original Research

Accepted on 31 Jan 2026

A Neutrosophic Explainable AI Framework for Modeling Uncertainty in Immersive Stereotactic Neurosurgical Simulation

in Artificial Intelligence in Neurology

Jesus Rafael Hechavarria-Hernandez

Frontiers in Neurology

553 views

Original Research

Accepted on 29 Jan 2026

AI-Assisted Screening for Mild Cognitive Impairment Using Routine EHR Data: A Gradient Boosting Approach

in Artificial Intelligence in Neurology

Tao Ye
Jianghua Peng

Frontiers in Neurology

116 views

Original Research

Published on 29 Jan 2026

Deep learning-based prediction of TERT mutation status from MRI for glioma molecular subtyping

in Artificial Intelligence in Neurology

Ting Zhu
Xuhao Dai
Xiaoqin Ge
Yuqing Hu
Jiangping Ren
Jiming Yang
Ruishuang Ma
Qingsong Tao

Frontiers in Neurology

doi 10.3389/fneur.2026.1749556

311 views

Original Research

Accepted on 27 Jan 2026

Machine learning-based risk of pulmonary embolism in stroke patients with 1 lower extremity deep vein thrombosis construction and validation of a prediction 2 model 3

in Artificial Intelligence in Neurology

Li Wu
Luoye Fangxin
Rong Liu
Wei Chen
Wanting Shi
Qiong Qin
Darong Lu
Jiexin Sheng

Frontiers in Neurology

108 views

Original Research

Accepted on 26 Jan 2026

Artificial Intelligence Policies in Neurology Journals: A Cross-Sectional Analysis

in Artificial Intelligence in Neurology

Kohl Kirby
Noah Calvert
Kaylyn Rowsey
Jillian Brassfield
Taylor Gardner
Patrick Crotty
Alec Young
Andrew Tran
Alicia Ito Ford
Matt Vassar

Frontiers in Neurology

180 views

Original Research

Accepted on 13 Jan 2026

EEFSA-SECM: An enhanced ensemble feature selection and stacking ensemble classifier to detect parkinson's disease

in Artificial Intelligence in Neurology

Vridhi Rajput
Maheswari N

Frontiers in Neurology

169 views

Original Research

Published on 13 Jan 2026

Deep transfer learning and explainable AI framework for autism spectrum disorder detection across multiple datasets

in Artificial Intelligence in Neurology

Shtwai Alsubai

Frontiers in Neurology

doi 10.3389/fneur.2025.1617446

869 views

Original Research

Published on 12 Jan 2026

Assessing the effectiveness of machine learning and deep learning in differentiating neuroimmunological diseases: a systematic review and meta-analysis

in Artificial Intelligence in Neurology

David Petrosian
Natasa Giedraitiene
Rasa Kizlaitiene
Dalius Jatuzis
Gintaras Kaubrys
Mantas Vaisvilas

Frontiers in Neurology

doi 10.3389/fneur.2025.1579206

1,055 views

Original Research

Published on 12 Jan 2026

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

in Artificial Intelligence in Neurology

Xiaoyu Tang
Min Tang
Wu Liu
Shaoyang Cui

Frontiers in Neurology

doi 10.3389/fneur.2025.1716984

866 views

Original Research

Published on 12 Jan 2026

Utilizing prior-data-fitted networks and in-context learning: a transformer-based tabular foundation model for predicting symptomatic intracranial hemorrhage after successful recanalization

in Artificial Intelligence in Neurology

Zheng Li
Jiayue Zhang
Chengbing Wang
Hui Wang
Penglun Sun
Fenglin Chen
Xiaohua Shi
Zhongxin Xu

Frontiers in Neurology

doi 10.3389/fneur.2025.1698741

477 views

Original Research

Published on 12 Jan 2026

Machine learning in developing a predictive model for chronic hydrocephalus following aneurysmal subarachnoid hemorrhage

in Artificial Intelligence in Neurology

Rao Dai
Enxi Xu
Lixiang Zhang
Zehui Wang
Bowen Liu
Siyuan Lu
Xiuhong Shan
Eryi Sun

Frontiers in Neurology

doi 10.3389/fneur.2025.1651694

689 views

Original Research

Published on 12 Jan 2026

AI-driven integration of imaging and radiology language improves stroke mortality prediction

in Artificial Intelligence in Neurology

Albara Alotaibi
Abdalla Moustafa
Laith Abualloush

Frontiers in Neurology

doi 10.3389/fneur.2025.1722965

1,009 views

Original Research

Published on 12 Jan 2026

Artificial intelligence in glioma research: a bibliometric analysis of global trends, hotspots, and future directions

in Artificial Intelligence in Neurology

Da Shao
Shulei Lou
Yunsheng Liu
Zengwei Kou

Frontiers in Neurology

doi 10.3389/fneur.2025.1701499

847 views

Original Research

Published on 07 Jan 2026

Development of an interpretable machine learning model for predicting venous thromboembolism in intensive care unit patients with intracerebral hemorrhage

in Artificial Intelligence in Neurology

Menghui He
Wenyan Liu
Zhongsheng Lu
Yiwei Lv
Qiang Zhang
Xiaoqing Jin
Pei Han

Frontiers in Neurology

doi 10.3389/fneur.2025.1691549

687 views

128 articles

articles

Construction and evaluation of a diagnostic prediction model for bacterial meningitis based on clinical and laboratory data

Interpretable machine learning for predicting 30-day mortality following intracranial hemorrhage surgery

Editorial: Technology Developments and Clinical Applications of Artificial Intelligence in Neurodegenerative Diseases

Convolutional Neural Networks: Applications, Challenges and Future Prospects in Brain Tumor Research

Causal Dynamic Decision-Making for Robotic Systems in Non-Markovian High-Difficulty Surgery

DenseLes: Slice-Wise Dense Network for Multiple Sclerosis Lesion Segmentation and Classication

Automatic and standardized reporting of perioperative MRIs in patients with central nervous system tumors

Machine learning models for predicting extended length of stay and hospital charges in nontraumatic subarachnoid hemorrhage

Deep learning and high-resolution magnetic resonance vascular wall imaging: current challenges and future perspectives

Artificial Intelligence-Driven Clinical Auxiliary Diagnosis of Benign Paroxysmal Positional Vertigo

A Neutrosophic Explainable AI Framework for Modeling Uncertainty in Immersive Stereotactic Neurosurgical Simulation

AI-Assisted Screening for Mild Cognitive Impairment Using Routine EHR Data: A Gradient Boosting Approach

Deep learning-based prediction of TERT mutation status from MRI for glioma molecular subtyping

Machine learning-based risk of pulmonary embolism in stroke patients with 1 lower extremity deep vein thrombosis construction and validation of a prediction 2 model 3

Artificial Intelligence Policies in Neurology Journals: A Cross-Sectional Analysis

EEFSA-SECM: An enhanced ensemble feature selection and stacking ensemble classifier to detect parkinson's disease

Deep transfer learning and explainable AI framework for autism spectrum disorder detection across multiple datasets

Assessing the effectiveness of machine learning and deep learning in differentiating neuroimmunological diseases: a systematic review and meta-analysis

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

Utilizing prior-data-fitted networks and in-context learning: a transformer-based tabular foundation model for predicting symptomatic intracranial hemorrhage after successful recanalization

Machine learning in developing a predictive model for chronic hydrocephalus following aneurysmal subarachnoid hemorrhage

AI-driven integration of imaging and radiology language improves stroke mortality prediction

Artificial intelligence in glioma research: a bibliometric analysis of global trends, hotspots, and future directions

Development of an interpretable machine learning model for predicting venous thromboembolism in intensive care unit patients with intracerebral hemorrhage