Page 16 - Read Online
P. 16

Page 31                                                            Landau et al. Art Int Surg. 2025;5:24-35  https://dx.doi.org/10.20517/ais.2024.78










































                Figure 3. Model of the relationship between relevant interrelated facets of the surgeon’s workflow (outer), within which core
                responsibilities (including operative time, collaboration with others, obligations related to hospital management, and maintenance of
                education and field knowledge) can be found. The goals of workflow components are specified (arrow ends). The image was created
                using Biorender.com.


               to craniofacial procedures. It is imperative to note that nearly half (n = 5, 45.5%) of the studies included in
               our review were published within 1 year of database query, which highlights the emergence of AI
               applications to billing and coding.


               Related specialties, such as orthopedic and general surgery, possess some established, tested, and
               documented models that may serve as a starting point for plastic and reconstructive surgery to utilize . A
                                                                                                      [30]
               Text Mining model performed superiorly in the context of spine surgery, which contains overlap with soft
               tissue flap-based closure performed in spino-plastic procedures. Hand surgery would likewise serve as an
               ideal candidate setting for implementing these AI methods with respect to procedural overlap of hardware
               use. Hand surgeons grapple with basal thumb arthritis and carpal tunnel syndrome as two of the most
               frequently encountered conditions , exhibiting unique overlap between plastic surgery and orthopedics, in
                                            [31]
               which the latter has demonstrated multiple NLP and ML technologies successfully integrated for medical
                     [10]
               coding .
               Intriguingly, the combined metrics for CPT code efficacy explored in this review proved consistently high
               and statistically similar for several technologies. Support vector machine (SVM), logistic regression (LR),
               Naïve Bayes (NB), and decision tree (DT) models all showed area under the receiver operating curve
               (AUROC) performance values > 0.98, where 1.00 or 100% represents perfect discriminative capabilities
               between right and wrong CPT codes. The expansive variety of procedures within gender-affirming surgery,
   11   12   13   14   15   16   17   18   19   20   21