Deep learning automation of radiographic patterns for hallux valgus diagnosis  

作　　者：Angela Hussain Cadence Lee Eric Hu Farid Amirouche 

机构地区：[1]Department of Orthopaedic Surgery,University of Illinois College of Medicine,Chicago,IL 60612,United States [2]Department of Orthopaedics Surgery,University of Illinois at Chicago,Chicago,IL 60612,United States [3]Department of Orthopaedic Surgery,Northshore University Health System,Skokie,IL 6007,United States

出　　处：《World Journal of Orthopedics》2024年第2期105-109,共5页世界骨科杂志（英文版）

摘　　要：Artificial intelligence(AI)and deep learning are becoming increasingly powerful tools in diagnostic and radiographic medicine.Deep learning has already been utilized for automated detection of pneumonia from chest radiographs,diabetic retinopathy,breast cancer,skin carcinoma classification,and metastatic lymphadenopathy detection,with diagnostic reliability akin to medical experts.In the World Journal of Orthopedics article,the authors apply an automated and AIassisted technique to determine the hallux valgus angle(HVA)for assessing HV foot deformity.With the U-net neural network,the authors constructed an algorithm for pattern recognition of HV foot deformity from anteroposterior highresolution radiographs.The performance of the deep learning algorithm was compared to expert clinician manual performance and assessed alongside clinician-clinician variability.The authors found that the AI tool was sufficient in assessing HVA and proposed the system as an instrument to augment clinical efficiency.Though further sophistication is needed to establish automated algorithms for more complicated foot pathologies,this work adds to the growing evidence supporting AI as a powerful diagnostic tool.

关 键 词：Artificial intelligence Hallux valgus Deep learning Automated radiography 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程] R684.3[医药卫生—骨科学]