Utilization of AI, Machine Learning, and Robotics in Vascular and Endovascular Neurosurgery

The field of neurosurgery is witnessing a paradigm shift with the integration of advanced technologies such as artificial intelligence (AI), machine learning, and robotic-assisted surgeries. These innovations are poised to revolutionize traditional neurosurgical techniques by enhancing precision, reducing risks, and improving patient outcomes. Recent studies have demonstrated promising results in utilizing AI for diagnostics and decision-making, machine learning algorithms for surgical planning, and robotics for precision-controlled operative interventions. Nevertheless, there is a pressing need to further investigate and understand how these technologies can be harmoniously incorporated into everyday neurosurgical practices, addressing current challenges and overcoming barriers to widespread adoption.

This Research Topic aims to explore the transformative impact of AI, machine learning, and robotics in neurosurgery. It seeks to uncover the extent to which these technologies can augment human capabilities and contribute to superior surgical outcomes. Key objectives include assessing the effectiveness of AI-driven diagnostic tools, testing hypotheses related to machine learning algorithms for procedural planning, and evaluating the real-time application of robotics during surgeries. Additionally, the research endeavors to identify potential obstacles, such as ethical considerations and practical limitations, that may impede the successful integration of these technologies.

To gather further insights into the boundaries of these technologies' applications in neurosurgery, we welcome articles addressing, but not limited to, the following themes:

-Development of innovative AI algorithms for surgical planning
-AI-driven diagnostic advancements in neuroscience
-Real-time robotic aids in neurosurgical operations
-Ethical implications and challenges of technology use in neurosurgery
-Comparative studies on traditional versus AI/robotic augmented neurosurgical techniques

We encourage submission of original research, reviews, case studies, and meta-analyses that delve into these and other related areas to foster a comprehensive understanding of the future of neurosurgery.

Topic Editor Erez Nossek is a consultant for Rapid Medical and a consultant and medical board member for Longeviti. Topic Editor Philipp Taussky is a consultant for Medtronic and a consultant for Cerenovenus.

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
• Clinical Trial
• Curriculum, Instruction, and Pedagogy
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

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

Article types

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

• Brief Research Report
• Case Report
• Clinical Trial
• Curriculum, Instruction, and Pedagogy
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: AI, neurovascular surgery, robotic-assisted surgery, machine learning, AI-driven diagnostics, ethical implications of AI in surgery

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.