Wu YC, Chang CY, Huang YT, Chen SY, Chen CH, Kao HK. Artificial Intelligence Image Recognition System for Preventing Wrong-Site Upper Limb Surgery.
Diagnostics (Basel) 2023;
13:3667. [PMID:
38132251 PMCID:
PMC10743305 DOI:
10.3390/diagnostics13243667]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 11/30/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023] Open
Abstract
Our image recognition system employs a deep learning model to differentiate between the left and right upper limbs in images, allowing doctors to determine the correct surgical position. From the experimental results, it was found that the precision rate and the recall rate of the intelligent image recognition system for preventing wrong-site upper limb surgery proposed in this paper could reach 98% and 93%, respectively. The results proved that our Artificial Intelligence Image Recognition System (AIIRS) could indeed assist orthopedic surgeons in preventing the occurrence of wrong-site left and right upper limb surgery. At the same time, in future, we will apply for an IRB based on our prototype experimental results and we will conduct the second phase of human trials. The results of this research paper are of great benefit and research value to upper limb orthopedic surgery.
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