Advancements in Artificial Intelligence for Foot and Ankle Surgery: A Systematic Review

Authors

Puneet Gupta, Department of Orthopaedic Surgery, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
Kiera A. Kingston, Hospital for Special Surgery, New York, NY, USA.
Martin O'Malley, Hospital for Special Surgery, New York, NY, USA.
Riley J. Williams, Hospital for Special Surgery, New York, NY, USA.
Prem N. Ramkumar, Hospital for Special Surgery, New York, NY, USA.

Document Type

Journal Article

Publication Date

1-1-2023

Journal

Foot & ankle orthopaedics

Volume

8

Issue

1

DOI

10.1177/24730114221151079

Keywords

ankle; artificial intelligence; foot; machine learning; orthopaedics; technology

Abstract

BACKGROUND: There has been a rapid increase in research applying artificial intelligence (AI) to various subspecialties of orthopaedic surgery, including foot and ankle surgery. The purpose of this systematic review is to (1) characterize the topics and objectives of studies using AI in foot and ankle surgery, (2) evaluate the performance of their models, and (3) evaluate their validity (internal or external validation). METHODS: A systematic literature review was conducted using PubMed/MEDLINE and Embase databases in December 2022. All studies that used AI or its subsets machine learning (ML) and deep learning (DL) in the setting of foot and ankle surgery relevant to orthopaedic surgeons were included. Studies were evaluated for their demographics, subject area, outcomes of interest, model(s) tested, model(s)' performance, and validity (internal or external). RESULTS: A total of 31 studies met inclusion criteria: 14 studies investigated AI for image interpretation, 13 studies investigated AI for clinical predictions, and 4 studies were grouped as "other." Studies commonly explored AI for ankle fractures, calcaneus fractures, hallux valgus, Achilles tendon pathologies, plantar fasciitis, and sports injuries. For studies reporting the area under the receiver operating characteristic curve (AUC), AUCs ranged from 0.64 (poor) to 0.99 (excellent). Two studies (6.45%) reported external validation. CONCLUSION: Applications of AI in the field of foot and ankle surgery are expanding, particularly for image interpretation and clinical predictions. Current model performances range from poor to excellent, and most studies lack external validation, demonstrating a need for further research prior to deploying AI-based clinical applications. LEVEL OF EVIDENCE: Level III, retrospective cohort study.

APA Citation

Gupta, Puneet; Kingston, Kiera A.; O'Malley, Martin; Williams, Riley J.; and Ramkumar, Prem N., "Advancements in Artificial Intelligence for Foot and Ankle Surgery: A Systematic Review" (2023). GW Authored Works. Paper 2405.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/2405

Department

School of Medicine and Health Sciences Student Works