Advances in Cardioneurology: Artificial Intelligence, Machine Learning and Prevention of Cardioneurological Complications

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About this Research Topic

Submission deadlines

  1. Manuscript Summary Submission Deadline 2 September 2025 | Manuscript Submission Deadline 21 December 2025

  2. This Research Topic is still accepting articles.

Background

Cardioneurology, the intersection of cardiac and neurological sciences, has become increasingly important due to the complex interactions between the cardiovascular system and the central nervous system. This research topic aims to explore recent advancements in the application of Artificial Intelligence (AI) and Machine Learning in cardioneurology for:
• Early Detection: Identifying cardioneurological complications at earlier stages.
• Risk Stratification: Classifying patient risk levels to improve treatment outcomes.
• Prevention: Developing strategies to prevent complications such as stroke, autonomic dysfunctions, hypoxic-ischemic encephalopathies, and cognitive impairments associated with cardiovascular diseases.

This topic also covers the development and validation of AI-based predictive models to improve clinical prognosis, optimize therapeutic decisions and personalize preventive interventions. In addition, it also addresses the investigation of the use of advanced algorithms for the analysis of large clinical databases, imaging exams, vital signs and biomarkers, promoting more accurate, preventive and personalized cardioneurological care.
We invite authors to submit manuscripts to this topic focused on, but not limited to:
• Ethical and Regulatory Issues: Addressing ethical considerations and regulatory frameworks in the use of AI in cardioneurology.
• Natural Language Processing: Leveraging NLP for electronic health record analysis.
• Machine Learning and Deep Learning: Exploring techniques in Cardioneurology.
• AI-Enabled Drug Discovery: Accelerating drug development processes.
• AI Algorithms for Detection, Treatment, Diagnosis, and Prognosis: Enhancing the full spectrum of patient management.
• AI-Based Biomarkers: Developing biomarkers for screening and diagnosis.
• AI-Assisted Imaging Analysis: Improving detection and segmentation accuracy.
• AI-Guided Treatment Planning: Enabling personalized therapy solutions.

Articles that are accepted for publication in this Research Topic following rigorous review by our external editors and external peer reviewers incur a publishing fee charged to paper authors, institutions, or funders.
The following types of manuscripts are invited for submission to this Topic:
• Research Articles: Original Research, Brief Research Reports, Clinical Trials, Case Reports, Case Studies.
• Review article: Review, Systematic Review, Mini Review
• Methods articles
• Study Protocols
• Other article types: Classifications, Opinions, Perspectives, General Commentaries.

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Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

  • Brief Research Report
  • Case Report
  • Classification
  • Clinical Trial
  • Community Case Study
  • Curriculum, Instruction, and Pedagogy
  • Editorial
  • General Commentary
  • Hypothesis and Theory

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: Cardioneurology, Artificial Intelligence (AI), Machine Learning, Risk Stratification, Predictive Models, Biomarkers, Personalized Care

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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