Artificial Intelligence in Surgical Planning: Optimizing Approaches for Humans and Animals
Code: G-1010
Authors: Mohammadmahdi Khajoueinejad * ℗, Roshanak Roshangah
Schedule: Not Scheduled!
Tag: Biomedical Signal Processing
Download: Download Poster
Abstract:
Abstract
Objective: This study examines the role of Artificial Intelligence (AI) in optimizing surgical planning in both human medicine and veterinary medicine, focusing on recent advancements, challenges, and future opportunities. Methods: A systematic review was conducted on 40 studies published between 2015 and 2023. The studies included experimental research, case studies, and comparative studies. Studies were evaluated using PRISMA criteria, and data were analyzed using qualitative content analysis. Results: Findings showed that AI implementation led to significant improvements in diagnostic accuracy (mean 93.5%) and reduction in image interpretation time (mean 45%). AI-driven simulations resulted in a 40% improvement in surgical outcome prediction and a 35% reduction in post-operative complications. In veterinary medicine, a 50% improvement in implant placement accuracy and a 40% increase in early tumor detection rates were observed. 80% of studies indicated potential for knowledge transfer between human and veterinary medicine. Conclusion: AI demonstrates significant potential to revolutionize surgical planning in both human and veterinary medicine. Key challenges include the need for high-quality data, privacy concerns, and the requirement for more extensive clinical evaluations. Future research should focus on developing more transparent algorithms, improving data quality, and conducting comprehensive clinical studies.
Keywords
Artificial Intelligence, Surgical Planning, Comparative Medicine
