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Artificial Intelligence in Surgeries

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venkat k
Artificial Intelligence in Surgeries

Objective:

The aim of this review is to summarize the main topics in Artificial Intelligence (AI), their applications and limitations in surgery. This paper reviews the key capabilities of AI services to help surgeons understand and critically assess new AI applications and contribute to new developments.

Summary of Background Data:

AI is composed of various sub-fields that provide potential solutions to each and every clinical problem. Each of the major subsets of AI reviewed in this piece has also been used in other industries, such as autonomous cars, social networks, and deep learning computers.

Methods:

A review of AI papers across computer science, statistics, and medical sources has been conducted to identify key concepts and technologies in AI that are innovating in industries including surgery. Limitations and challenges for working with AI are also reviewed.

Results:
Four main sub-fields of AI are defined:

  1. machine learning
  2. artificial neural networks,
  3. natural language processing and
  4. computer vision.

Their current and future applications have been introduced to surgical practice, including big data analytics and clinical decision support systems. The role of surgeons in the development of technology to optimize the implications and clinical impact of AI to surgeons is discussed.

Conclusion:
Surgeons are well-positioned to help integrate AI into modern practice. Surgeons must partner with data scientists to capture data and provide a clinical context for the stages of care, as AI has the potential to revolutionize the way surgery is taught and practiced.

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venkat k
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