ArticleIndian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India2024
Advancements in Skull Base Surgery: Navigating Complex Challenges with Artificial Intelligence.
Article in Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Simulators with Haptic Feedback in Neurosurgery: Are We Reaching the "Aviator" Type of Training? Narrative Review and Future Perspectives.Life (Basel, Switzerland) · 2025Review
- Sphenoid sinus hyperpneumatization: anatomical variants, molecular blueprints, and AI-augmented roadmaps for skull base surgery.Frontiers in endocrinology · 2025Review
- A comparison between robot-assisted minimally invasive surgery and conventional craniotomy for intracerebral hemorrhage: efficiency, complications and outcomes.Frontiers in neurology · 2025Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This narrative review examines the evolving landscape of artificial intelligence (AI) integration in skull base surgery, exploring its multifaceted applications and impact on various aspects of patient care. Methods: Extensive literature review was conducted to gather insights into the role of AI in skull base surgery. Key aspects such as diagnosis, image analysis, surgical planning, navigation, predictive analytics, clinical decision-making, postoperative care, rehabilitation, and virtual simulations were explored. Studies were sourced from PubMed using keyword search strategy for relevant headings, sub-headings and cross-referencing. Results: AI enhances early diagnosis through diagnostic algorithms that guide investigations based on clinical and radiological data. AI-driven image analysis enables accurate segmentation of intricate structures and extraction of radiomics data, optimizing preoperative planning and predicting treatment response. In surgical planning, AI aids in identifying critical structures, leading to precise interventions. Real-time AI-based navigation offers adaptive guidance, enhancing surgical accuracy and safety. Predictive analytics empower risk assessment, treatment planning, and outcome prediction. AI-driven clinical decision support systems optimize resource allocation and support shared decision-making. Postoperative care benefits from AI's monitoring capabilities and personalized rehabilitation protocols. Virtual simulations powered by AI expedite skill development and decision-making in complex procedures. Conclusion: AI contributes to accurate diagnosis, surgical planning, navigation, predictive analysis, and postoperative care. Ethical considerations and data quality assurance are essential, ensuring responsible AI implementation. While AI serves as a valuable complement to clinical expertise, its potential to enhance decision-making, precision, and efficiency in skull base surgery is evident.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.