Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stroke: Introduction and Types01:29

Stroke: Introduction and Types

A stroke is an acute neurological event caused by the sudden disruption of cerebral blood flow, leading to rapid loss of neuronal function. Neurons depend on continuous oxygen and glucose supply, so even brief interruptions can cause irreversible injury within minutes. Strokes are classified into ischemic and hemorrhagic types.Ischemic StrokeIschemic strokes are most common and occur due to arterial occlusion, depriving brain tissue of oxygen and nutrients. This leads to energy failure, ionic...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Development of an Intelligent Clinical Decision Support System for Spirometry Quality Control.

Diagnostics (Basel, Switzerland)·2026
Same author

Artificial Intelligence Applications in Chronic Obstructive Pulmonary Disease: A Global Scoping Review of Diagnostic, Symptom-Based, and Outcome Prediction Approaches.

Biomedicines·2025
Same author

Artificial Intelligence for Spirometry Quality Evaluation: A Systematic Review.

Bioengineering (Basel, Switzerland)·2025
Same author

Convolutional Neural Network-Based Approach for Cobb Angle Measurement Using Mask R-CNN.

Diagnostics (Basel, Switzerland)·2025
Same author

Predicting COPD Readmission: An Intelligent Clinical Decision Support System.

Diagnostics (Basel, Switzerland)·2025
Same author

Proposal and Definition of an Intelligent Clinical Decision Support System Applied to the Prediction of Dyspnea after 12 Months of an Acute Episode of COVID-19.

Biomedicines·2024
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 15, 2026

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
09:42

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Published on: September 1, 2023

1.2K

Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis.

João N D Fernandes1,2,3, Vitor E M Cardoso4,3, Alberto Comesaña-Campos5,6

  • 1INESC TEC, 4200-465 Porto, Portugal.

Sensors (Basel, Switzerland)
|July 13, 2024
PubMed
Summary
This summary is machine-generated.

Machine learning and deep learning show promise for predicting brain stroke (cerebrovascular accident) risks and improving patient care. This review analyzes AI applications in stroke diagnosis and highlights future research directions for better health monitoring.

Keywords:
brain strokeclassificationdeep learningmachine learningobject detectionsegmentation

More Related Videos

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

48.0K
Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
12:50

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

40.2K

Related Experiment Videos

Last Updated: Jun 15, 2026

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
09:42

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Published on: September 1, 2023

1.2K
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

48.0K
Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
12:50

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

40.2K

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Neurology

Background:

  • Brain stroke (cerebrovascular accident) is a leading cause of death and disability worldwide.
  • Accurate prediction and diagnosis of stroke are crucial for effective management and patient outcomes.
  • Existing analytical methods struggle with the complexity of stroke risk factors.

Purpose of the Study:

  • To comprehensively review machine learning (ML) and deep learning (DL) applications in brain stroke diagnosis.
  • To identify current challenges and future research directions in AI-driven stroke analysis.
  • To provide a curated list of relevant datasets for brain stroke research.

Main Methods:

  • Systematic review of 25 review papers published between 2020-2024, adhering to PRISMA guidelines.
  • Focus on ML/DL applications in stroke classification, segmentation, and object detection.
  • Evaluation of advanced sensor systems for predictive health monitoring.

Main Results:

  • ML and DL techniques offer advanced data processing for identifying stroke predictors.
  • These AI methods enhance diagnostic accuracy and enable personalized care recommendations.
  • The review synthesizes findings on performance evaluation and validation of AI models.

Conclusions:

  • AI, particularly ML and DL, holds significant potential to transform brain stroke diagnosis and patient care.
  • Further research is needed to address current challenges and optimize AI applications in neurology.
  • Advanced sensor systems integrated with AI can improve predictive health monitoring for stroke.