NDLI: Augmented Intelligence in Joint Replacement Surgery: How can artificial intelligence (AI) bridge the gap between the man and the machine?

Content Provider	Springer Nature : BioMed Central
Author	Bagaria, Vaibhav Tiwari, Anjali
Abstract	Robot-assisted arthroplasty is likely to grow exponentially in the years to come. While most surgeons recognize their superiority in refining alignment and improving component positioning accuracy, the universal adaptability of robots remains slow due to certain technological and behavioural gaps. Endoprosthesis robots currently suffer from increased reaction time, lack of natural adaptation to the surgeon's abilities, and unavailability and inapplicability in different surgical contexts. As humans and machines have to move forward into the next phase of their relationship, robots enabled with artificial intelligence (AI) may become more advanced and an alternative to overcome existing challenges like cost, training, and improve performance based on feedback provided by surgeons. Augmented intelligence is perhaps a more apt word than artificial, as it reflects more human-machine fusion and several areas are already proactively adopting the terminology. Arthroplasty robots can benefit from AI by using computer vision models, applying sensors, and integrating feedback and loop execution. All of this would help achieve a technical superiority to the surgeon alone. This brief perspective on how humans and machines are likely to benefit from the integration of AI outlines the technical side of this enablement.
Related Links	https://arthroplasty.biomedcentral.com/counter/pdf/10.1186/s42836-021-00108-1.pdf
Ending Page	4
Page Count	4
Starting Page	1
File Format	HTM / HTML
ISSN	25247948
DOI	10.1186/s42836-021-00108-1
Journal	Arthroplasty
Issue Number	1
Volume Number	4
Language	English
Publisher	BioMed Central
Publisher Date	2022-02-02
Access Restriction	Open
Subject Keyword	Orthopedics Artificial intelligence Arthroplasty Robotics Machine learning Interface
Content Type	Text
Resource Type	Article
Subject	Orthopedics and Sports Medicine Surgery
Journal Impact Factor	2.3/2023
5-Year Journal Impact Factor	2.3/2023

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