Artificial Intelligence Image Recognition System for Preventing Wrong-Site Upper Limb Surgery

Author:

Wu Yi-Chao1ORCID,Chang Chao-Yun2,Huang Yu-Tse2,Chen Sung-Yuan2,Chen Cheng-Hsuan34ORCID,Kao Hsuan-Kai567

Affiliation:

1. Department of Electronic Engineering, National Yunlin University of Science and Technology, Yunlin 950359, Taiwan

2. Interdisciplinary Program of Green and Information Technology, National Taitung University, Taitung 950359, Taiwan

3. Department of Electrical Engineering, National Central University, Taoyuan 320317, Taiwan

4. Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City 242062, Taiwan

5. Department of Orthopedic Surgery, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan

6. Bone and Joint Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan

7. College of Medicine, Chang Gung University, Taoyuan 333423, Taiwan

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.

Publisher

MDPI AG

Subject

Clinical Biochemistry

Reference35 articles.

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