Abstract
The purpose of this study is to provide a comprehensive review of recent trends in podiatric and orthopedic foot and ankle literature related to artificial Intelligence (AI). By analyzing the volume and progression of research publications over the past decade, this study aims to characterize the integration and interest of AI in this specialized field. Articles referencing AI within the field of podiatric and orthopedic foot and ankle surgery were retrieved from the top 10 SCImago-ranked journals focused on the foot and ankle. The search query “Artificial Intelligence” was entered into the general search bar for each journal. A thorough review was then conducted. Articles were further broken down into research design types. Inclusion criteria for analysis included research articles related to or specifically about AI which were deemed relevant following independent review. All abstract only papers, editorials, and those listed as “other” were excluded from analysis. Journals were then subdivided by specialty into Podiatric and Orthopedics, as defined by the Editor-in-Chief’s professional degree, revealing no significant difference in relevance of AI-related articles between the two groups ( P = 0.4921). The journal Foot and Ankle Surgery had the highest percentage of relevant articles at 70.83%. Analysis demonstrated a marked increase in AI-related publications over the past decade, with a sharp rise in the past two years (2.78% in 2015 to 33.33% in 2025). These findings underscore a notable increase in AI-focused research within podiatric and orthopedic literature, reflecting a growing interest in AI’s potential to enhance both clinical practice and research. The authors encourage further investigation into this topic.
Introduction
Artificial Intelligence (AI) has rapidly emerged as an evolving tool with numerous applications throughout the field of medicine. As computational power and data accessibility have increased, the integration of AI into clinical research and practice has accelerated dramatically over the last decade. AI systems are now embedded in many aspects of day to day care such as drafting clinical notes, flagging at-risk patients, routing patient messages, and have roles within practice revenue cycle management. , Recent investigations within foot and ankle surgery have similarly demonstrated growing clinician interaction with artificial intelligence tools for research generation, manuscript evaluation, and clinical information synthesis. ,, This momentum reflects not only the technological advancement but also the growing recognition within the medical community of AI’s capacity to augment and support a physician throughout clinical research and practice.
Within the realm of foot and ankle surgery, both podiatric and orthopedic literature has begun exploring the application of AI in various use cases within the field. ,, As such, understanding how AI research has developed within these intersecting specialties is essential to help guide future integration of this technology.
Bibliometric analysis offers a systematic approach to evaluating research output and trends within a field over time. Prior studies evaluating artificial intelligence within foot and ankle literature have largely focused on AI performance evaluation rather than publication trends, leaving a gap in the current literature and a need for bibliometric assessment of research growth. , By quantifying publication volume, we gain valuable insight into how readily the field may be adopting these emerging technologies. Applying this method to podiatric and orthopedic literature allows for an objective assessment of the growing influence of AI and the rate at which it is being incorporated into academic and clinical research.
This study aims to provide a comprehensive review of recent trends in podiatric and orthopedic foot and ankle literature related to AI. By analyzing publications from the top SCImago-ranked foot and ankle journals, this research evaluates the publication interests of AI within these specialties. The primary objective was to evaluate the volume and progression of AI focused publications over time, with a secondary objective of comparing publication trends between podiatric and orthopedic journals.
Methods
To ensure a high quality data set, the top ten SCImago-ranked foot and ankle journals were queried. These journals were selected based on their impact metrics within the SCImago journal rank (SJR) database. Journals were categorized as podiatric or orthopedic based on the professional degree of the Editor-in-Chief (DPM or MD/DO, respectively), reflecting the primary professional community served by the journal.
A systematic search was conducted within each selected journal’s online database. The search query “Artificial Intelligence” was entered into the general search bar for each journal. The search was not restricted and included each journal’s entire history. All articles returned by this search were reviewed for inclusion. Inclusion criteria consisted of research articles and review papers that specifically referenced or investigated artificial intelligence within the context of foot and ankle surgery. Articles were deemed relevant following independent review by two separate investigators. These two investigators independently screened articles for eligibility. Disagreements were resolved through discussion and consensus. Exclusion criteria included abstracts without full papers, editorials, letters to editors, conference proceedings, and articles classified as “other”. Discrepancies in article classification were resolved through further investigation and discussion until consensus was reached.
For each included publication, bibliographic information was extracted, including journal name, year of publication, article type, and study design. Articles were then classified according to research design. The proportion of AI-related publications relative to the total number of published articles that populated per journal and per year was calculated.
Bibliometric data was then analyzed to identify publication trends over time and differences between podiatric and orthopedic journals. The frequency and percentage of AI-related articles were calculated for each journal and each publication year. Comparative analysis between podiatric and orthopedic journal groups was performed using Fisher exact test, with statistical significance set at p < 0.05. All statistical analyses were conducted using Microsoft Office Excel (Microsoft, Redmond, WA).
Results
Ten journals were analyzed, comprising four orthopedic, five podiatric, and one interdisciplinary journal (Foot and Ankle Specialist). Across all journals, a total of 129 screened articles were reviewed, of which 36 (27.9%) were identified as relevant to AI based on inclusion criteria ( Fig. 1 ).
Flow diagram illustrating the number of articles considered at each stage of the review process.
Among individual journals, Foot and Ankle Surgery demonstrated the highest proportion of AI-related articles (17/24, 70.83%), followed by Foot & Ankle Specialist (4/9,44.44%), and The Journal of Foot & Ankle Surgery (3/7, 42.86%). In contrast, the journal Foot and Ankle Clinics (1/22, 4.54%), and the journal Foot (0/4, 0%) contained the fewest AI-related screened publications ( Table 2 ).
When the number of AI-related articles identified in this review was compared with the total publication output of each journal, AI-focused research represented a very small proportion of the overall literature. Across all journals examined, AI-related publications accounted for <1% of the total articles published in each journal’s history. The journal of Foot and Ankle Surgery demonstrated the highest relative representation, with 17 relevant articles corresponding to approximately 0.77% (17) of its 2198 total publications. Foot & Ankle Specialist and Foot and Ankle Orthopedics also demonstrated comparatively higher representation, with AI-related articles accounting for 0.36% (4/1102) and 0.30% (5/1664) of their total publications, respectively ( Table 2 ).
In contrast, several journals demonstrated extremely limited representation of AI-focused work when compared to their total publication volume. For example, Foot and Ankle International contained only 2 AI-related articles among 6389 total publications (0.03%), while The Journal of Foot and Ankle Surgery contained 3 AI-related articles among 4225 total publications (0.07%). Similarly, Clinics in Podiatric Medicine and Surgery and Journal of American Podiatric Medical Association demonstrated AI-related publication rates of 0.06% (1/1653) and 0.02% (1/4458), respectively, and the journal Foot contained no AI-related publications (0/1656) ( Table 2 ).
When grouped by specialty, orthopedic journals (n = 4) produced 25 relevant AI-related articles out of 87 total screened publications (28.7%), while podiatric journals (n = 5) produced 7 relevant articles out of 33 total screened publications (21.2%). Statistical analysis revealed no significant difference in the proportion of AI-related publications between orthopedic and podiatric journals ( p = 0.4921). Notably, Foot and Ankle Specialist, which features both orthopedic and podiatric Co-Editor-in-Chief, demonstrated an intermediate relevance of 44.4% ( Table 1 , 2 ).
Table 1
The evaluated journals subdivided into specialties defined by the Editor-in-Chief’s professional degree.
| Orthopedic Journals: | |
|---|---|
| 1. Foot and Ankle International (FAI) | |
| 2. Foot and Ankle Surgery | |
| 3. Foot and Ankle Clinics | |
| 4. Foot and Ankle Orthopedics | |
| Podiatric Journals: | |
| 1. Journal of Foot and Ankle Research | |
| 2. Journal of Foot and Ankle Surgery (JFAS) | |
| 3. Foot | |
| 4. Clinics in Podiatric Medicine | |
| 5. Journal of American Podiatric Medical Association (JAPMA) | |
| Interdisciplinary: | |
| 1. Foot and Ankle Specialist |
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