About this Research Topic
Artificial Intelligence (AI) in Precision Cardioneurology is an emerging interdisciplinary field that integrates advanced AI technologies with cardiology and neurology to enhance patient care. The current landscape of Cardioneurology faces significant challenges, including the complexity of diagnosing and treating conditions that overlap between the heart and brain. Recent studies have shown promising results in using AI for early detection, diagnosis, and personalized treatment plans, yet there remain substantial gaps in fully understanding and implementing these technologies. Ongoing debates focus on the ethical and regulatory implications of AI in healthcare, the accuracy and reliability of AI algorithms, and the integration of AI with existing medical practices. Despite these advancements, there is a pressing need for more comprehensive research to address these gaps and to develop robust, clinically applicable AI solutions.
This research topic aims to explore and expand the applications of artificial intelligence in Precision Cardioneurology. The primary objectives include investigating how AI can improve the detection, diagnosis, treatment, and prognosis of Cardioneurological conditions. Specific questions to be addressed include: How can AI algorithms be optimized for better accuracy in Cardioneurology? What are the ethical and regulatory challenges in implementing AI in this field? How can AI contribute to personalized therapy and treatment planning?
To gather further insights in the integration of AI in Precision Cardioneurology, we welcome articles addressing, but not limited to, the following themes:
- Ethical and regulatory issues in AI in Cardioneurology
- Natural language processing for electronic health record analysis
- Machine learning and deep learning in Cardioneurology
- AI-enabled drug discovery and development
- AI algorithms for Cardioneurology for detection, treatment, diagnosis, and prognosis
- AI-based biomarkers for Cardioneurology screening and diagnosis
- AI-assisted imaging analysis for Cardioneurology detection and segmentation
- AI-guided treatment planning and personalized therapy
This research topic aims to explore and expand the applications of artificial intelligence in Precision Cardioneurology. The primary objectives include investigating how AI can improve the detection, diagnosis, treatment, and prognosis of Cardioneurological conditions. Specific questions to be addressed include: How can AI algorithms be optimized for better accuracy in Cardioneurology? What are the ethical and regulatory challenges in implementing AI in this field? How can AI contribute to personalized therapy and treatment planning?
To gather further insights in the integration of AI in Precision Cardioneurology, we welcome articles addressing, but not limited to, the following themes:
- Ethical and regulatory issues in AI in Cardioneurology
- Natural language processing for electronic health record analysis
- Machine learning and deep learning in Cardioneurology
- AI-enabled drug discovery and development
- AI algorithms for Cardioneurology for detection, treatment, diagnosis, and prognosis
- AI-based biomarkers for Cardioneurology screening and diagnosis
- AI-assisted imaging analysis for Cardioneurology detection and segmentation
- AI-guided treatment planning and personalized therapy
Keywords: AI, Artificial Intelligence, Precision Cardiology, Precision Cardioneurology
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.
