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Page 215 Dababneh et al. Art Int Surg 2024;4:214-32 https://dx.doi.org/10.20517/ais.2024.50

INTRODUCTION
Recent advancements in artificial intelligence (AI) have significantly driven its integration into numerous
medical and surgical fields, enhancing diagnostic accuracy and improving patient care. The notion of AI
was initially introduced by John McCarthy, an American computer scientist, in 1956 . Since then, AI has
[1]
branched out into various fields, such as machine learning (ML), deep learning (DL), natural language
[2]
processing (NLP), and robotics . ML makes predictions based on the detection of patterns in data. When
trained on labeled data, it is considered supervised learning and its implications in medicine include data
classification for diagnostic purposes and outcome predictions. On the other hand, unsupervised learning
consists of ML algorithms trained with unlabeled data. The goal of unsupervised learning is to identify
[3]
hidden patterns within the data without predefined outcomes . Clinical applications for such algorithms
include the identification of disease risk factors . Given these various applications and the significant
[4]
potential of ML in improving care, extensive efforts are underway to facilitate its integration in clinical
settings . As for DL, it is a branch of ML that uses multiple layers of neural networks to enhance the
[5]
accuracy of pattern recognition . It is particularly useful in the analysis of medical images, facilitating the
[2]
[6]
diagnosis process . Therefore, to date, medical imaging is the medical field that has benefitted the most
from AI development . In this area, ML is used to enhance diagnostic accuracy and efficiency. Finally,
[7,8]
[2,6]
NLP, another branch of ML, has the potential to understand and interpret words and provide a response .
In surgical fields, AI has been shown to increase precision, reduce errors, and optimize preoperative
planning and operating room workflow . Furthermore, it has the capability to predict surgical outcomes
[9]
and postoperative complications . Considering its significant potential to improve patient care, increased
[10]
research is currently being done to determine its application in different surgical fields, including plastic
surgery. AI is becoming increasingly valuable in plastic surgery, especially for tasks requiring visual
diagnosis, such as assessing preoperative and postoperative aesthetics . Similarly, ML algorithms have also
[11]
been used to improve outcome assessments in various procedures, such as rhinoplasty [12,13] . Additionally,
facial recognition tools, a subtype of supervised learning in ML, have the potential to demonstrate the
projected results of aesthetic surgeries, thereby assisting in managing patient expectations [2,14] .

Few systematic reviews have explored the role of AI in plastic surgery in recent years [2,3,11,13] . While these
reviews provide medical professionals with valuable insights into the emerging applications of AI across
various fields of plastic surgery, they also highlight the need for further research in certain areas. Notably,
Mantelakis et al. noted a significant gap in AI research related to hand surgery and the use of ML in this
[3]
domain . In addition, three [2,3,11] of the four systematic reviews were limited to articles published up to 2020,
and the fourth covered articles up to 2021. Given the rapidly increasing literature on the applications of
[13]
AI in medicine, the aim of this systematic review was to provide a comprehensive analysis of its application
within the field of hand and wrist surgery.

METHODS
A comprehensive literature search was conducted across PubMed, Embase, Medline and Cochrane libraries,
[15]
adhering to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines .
The search focused on identifying articles related to the application of AI in hand surgery, using multiple
relevant keywords. Each identified article was assessed based on its title, abstract, and full text. The primary
search was conducted on August 6, 2024, utilizing the following keywords in articles’ titles and abstracts:
“Artificial Intelligence” OR “Computer-Aid” OR “Machine learning” OR “ChatGPT” along with specific
terms related to hand surgery such as “hand surgery” OR “wrist surgery” OR “plastic surgery” OR “wrist”
OR “finger” OR “Peripheral Nerve Surgery” OR “scaphoid” OR “carpal bone” OR “thumb”. A variety of