Published November 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Surgical Data Science and Associated Techniques Facilitate the Development of Contemporary Equipment like Apple's Vision Pro

Creators

  • 1. Department of Data Science, Stevens Institute of Technology, Seattle, WA, (United States of America) USA.

Contributors

Contact person:

  • 1. Department of Data Science, Stevens Institute of Technology, Seattle, WA, (United States of America) USA.
  • 2. Stevens Institute of Technology, Philadelphia, PA, (United States of America) USA.
  • 3. Department of Computer Science, University of North Carolina at Charlotte, Seattle, WA, (United States of America) USA.
  • 4. Department of Computer Science, Stevens Institute of Technology, Texas, TX, (United States of America) USA.
  • 5. Department of Civil Engineering, Syracuse University, Charlotte, (United States of America) USA.

Description

Abstract: Artificial Intelligence (AI) has revolutionized modern surgery by enhancing every stage of patient care, from preoperative planning to postoperative monitoring. This paper explores the impact of AI in conjunction with other technologies in surgical procedures, emphasizing their empirical basis and integration into clinical practice. AI's role in facilitating personalized treatment planning through a comprehensive analysis of patient data and imaging studies, utilizing techniques like natural language processing (NLP) to extract critical insights, reassures us of its positive impact on patient care. Real-time decision support systems powered by AI improve surgical precision, enabling surgeons to navigate complex procedures with enhanced accuracy and efficiency. Furthermore, AI-driven surgical robotics exemplify the precision achievable with these technologies, enabling minimally invasive procedures that minimize patient trauma and expedite recovery. Integrating AI with computer vision further enhances surgical capabilities by allowing machines to interpret visual data autonomously, like human perception. Convolutional Neural Networks (CNNs) are pivotal in image recognition and analysis, supporting tasks from anatomical landmark identification to surgical planning. Augmented Reality (AR), when combined with AI, enriches surgical practice by overlaying digital information onto real-world views, aiding in intraoperative guidance and educational training. Devices like Apple's Vision Pro (AVP) headset showcase the potential of mixed reality technologies in enhancing surgical precision. AVP's integration of spatial computing and AI algorithms allows for real-time data analysis and decision support, transforming surgical education and procedural outcomes. Despite the transformative potential, challenges, including ethical considerations, data privacy, and regulatory frameworks, must be addressed to ensure the responsible deployment of AI in surgical settings. These challenges include mitigating biases in AI algorithms and ensuring equitable access to advanced technologies across diverse surgical specialties. The dynamic nature of AI in surgery necessitates continued research and development to refine AI applications, optimize surgical workflows, and improve patient outcomes globally. In combination with contemporary technologies, AI represents a paradigm shift in surgical practice, offering unprecedented opportunities to enhance patient care through personalized, precise, and efficient interventions. AI's ongoing evolution and integration in surgery promise to reshape healthcare's future, advancing clinical practice and medical education toward safer, more effective, and inclusive healthcare delivery systems.

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Additional details

Identifiers

DOI
10.54105/ijpmh.D3648.0501124
EISSN
2582-7588

Dates

Accepted
2024-11-15
Manuscript received on 21 August 2024 | Revised Manuscript received on 02 November 2024 | Manuscript Accepted on 15 November 2024 | Manuscript published on 30 November 2024.

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