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Page 225 Dababneh et al. Art Int Surg 2024;4:214-32 https://dx.doi.org/10.20517/ais.2024.50

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developing a ML model to predict symptom improvement following CTD . GBM was the highest-
performing model, achieving an AUC of 0.723.

Loos et al. compared the ability of hand surgeons to predict symptom improvement after CTD with that of
[73]
AI models . The hand surgeons achieved an accuracy rate of 0.65 with an AUC of 0.62. In contrast, the AI
prediction model achieved a higher accuracy rate of 0.78 with an AUC of 0.77. It is important to note that
the AI prediction model had access to several patient-reported outcome measures to complete its task. This
information is not routinely compiled by hand surgeons, which could contribute to the difference in
performance noted between the two groups.

AI-assisted surgery
AI as an adjunctive in wrist arthroscopy
Orgiu et al. developed an AI algorithm to help identify carpal bone structures during wrist arthroscopy .
[74]
The researchers collected and labeled images from 20 procedures to train and test a DeepLabv3+
classification algorithm. Their model achieved an average Dice score of 89%, indicating that it can effectively
assist in identifying carpal bone structures during wrist arthroscopy. Nevertheless, the algorithm’s
performance varied among different bones, with some such as the capitate and triquetrum achieving high
accuracy rates, while others including the scaphoid and lunate showed moderate results.

Robotics in microsurgery
Henn et al. provide an overview of the current status, advancements, challenges, and future prospects of
[75]
robotic surgery in plastic surgery . The da Vinci surgical system is highlighted as the most popular
platform, widely used across multiple surgical disciplines for its articulated robotic arms and enhanced
imaging capabilities. Specific applications in plastic and hand surgery include automated or assisted
microvascular anastomosis. Despite its benefits, there are several limitations to the adoption of robotic
surgery, including its high initial costs and the need for specialized training for its effective use, as well as
the ethical and legal concerns regarding accountability and patient safety.

Integrating AI in hand and wrist surgery training
In 2023, Mohapatra et al. explored the role of AI, specifically LLM, such as ChatGPT, in the training of
plastic surgery residents . The authors identified several teaching assistant (TA) tasks that LLMs can
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perform, including generating interactive case studies, simulating preoperative consultations, and
formulating ethical considerations. ChatGPT was found to be capable of assisting faculty with classroom
instructions, grading papers, and providing feedback on assignments. Clarity and usefulness constituted
AI’s biggest strengths, particularly in simulating preoperative consultations. However, when analyzing
ChatGPT’s ability to provide step-by-step guidance for procedures such as microsurgical arterial
anastomosis, evaluators noted that while AI provided accurate steps, it omitted some critical components
and generated certain inaccurate statements, potentially leading to resident confusion.

AI-assisted patient education
Our review identified five articles focused on the use of AI for patient communication purposes. Jagiella-
Lodise et al. evaluated the widest variety of conditions, including CTS, Dupuytren contracture, De Quervain
tenosynovitis, trigger finger and metacarpal arthritis . The authors looked to evaluate the accuracy and the
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completeness of answers provided by ChatGPT 3.5 when questioned on symptoms, pathology,
management, surgical indications, recovery time, insurance coverage, and worker’s compensation
availability. Their findings suggest that ChatGPT’s overall answers were adequate, but not complete, which
led to a lack of comprehension. Amen et al. also tasked ChatGPT with answering common questions asked
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by patients suffering from CTS . The authors concluded that ChatGPT provided overall reliable and easily