The intersection of cardiac and neuroscience, cardiometagraphies are becoming increasingly important due to the complex interactions between the cardiovascular and central nervous systems. This research topic aims to explore recent advances in the application of cardiology's artificial intelligence (AI) and machine learning.
•Early detection: Identifying cardiac complications at previous stages.
• Risk stratification: Classifies patient risk levels to improve treatment outcomes.
• Prevention: Development of strategies to prevent complications such as stroke, autonomic dysfunction, hypoxic ischemic encephalopathy, and cognitive impairments associated with cardiovascular disease.
This topic also covers the development and validation of AI-based predictive models to improve clinical prognosis, optimize therapeutic decisions, and personalize preventive interventions. Additionally, it addresses investigations into the use of advanced algorithms for large-scale clinical databases, imaging tests, vital signs, and biomarker analysis, facilitating more accurate, preventive and personalized cardiac uurological care.
We invite the authors to submit manuscripts focusing on this topic, but not limited to:
•Ethical and regulatory issues: Addressing ethical considerations and regulatory frameworks in the use of AI in Cardioneurology.
•Natural Language Processing: Utilizes NLP for electronic health record analysis.
• Machine learning and deep learning: Cardiology exploration techniques.
• AI-enabled creation: Accelerating the drug development process.
• Detection, treatment, diagnosis, and prognosis AI algorithms: Enhance the full scope of patient management.
•AI-based biomarkers: Development of biomarkers for screening and diagnosis.
•AI-assisted imaging analysis: Improved detection and segmentation accuracy.
•AI-guided treatment plans: Enabling personalized treatment solutions.
Following strict reviews by external editors and external peer reviewers, articles accepted to be featured on this research topic will receive a publication fee charged to the paper author, institution, or funder.
The following types of manuscripts are invited to submit to this topic:
• Research article: Original research, brief research report, clinical trials, case reports, case studies.
•Review Articles: Reviews, Systematic Reviews, Mini Reviews
Method Article
Research protocol
•Other article types: Classification, opinions, perspectives, general commentary.
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
keyword: Cardiology, 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 submitted sections and journals, as defined in the mission statement. Frontier reserves the right to direct out-of-scope manuscripts into a more appropriate section or journal at any stage of peer review.
