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Brenac et al. Art Int Surg 2024;4:296-315  https://dx.doi.org/10.20517/ais.2024.49                                                                                                                                                       Page 306



                                            (2) Patients reported a greater perceived age reduction
                                            (-6.7 years) compared to the neural network estimates
                                            (-4.3 years)
                                            (3) FACE-Q scores indicated high patient satisfaction
                                            with facial appearance, quality of life, and overall
                                            outcome
                                            (4) A positive correlation was found between neural
                                            network age reduction estimates and patient satisfaction
 Boonipat   Using artificial intelligence to   2020 Plastic and   (1) Evaluate the use of ML to measure facial   (1) The facial recognition application showed a greater
 et al. [40]  measure facial expression following   Reconstructive   expression before and after facial reanimation   recognition of happy signals in postoperative (42%) vs.
 facial reanimation surgery  Surgery  surgery using video data  preoperative (13%) smile videos (P < 0.0001) compared
                                            to 53% in control videos
 [41]
 Geisler et al.  A role for artificial intelligence in   2021 Journal of   (1) Develop CNN models based on the ResNet-50  (1) CNN model developed showed an overall testing
 the classification of craniofacial   Craniofacial   architecture to classify non-syndromic CS from 2D  accuracy of 90.6%, demonstrating the potential of ML to
 anomalies  Surgery  clinical photographs   detect craniofacial conditions
 Knoops   A machine learning framework for   2019 Scientific Reports  (1) Develop the first fully automated large-scale   (1) The developed 3DMM achieves a diagnostic
 [42]
 et al.  automated diagnosis and   clinical 3DMM for supervised learning in   sensitivity of 95.5% and specificity of 95.2%
 computer-assisted planning in   diagnostics, risk stratification, and treatment   (2) The model simulates surgical outcomes with a mean
 plastic and reconstructive surgery  simulation, and to demonstrate its potential for   accuracy of 1.1 ± 0.3 mm
 improving clinical decision making in orthognathic  (3) The 3DMM framework automates diagnosis and
 surgery                                    provides patient-specific treatment plans from 3D scans,
                                            improving efficiency in clinical decision making
 [44]
 Lim et al.  Using generative artificial   2023 Journal of Clinical   (1) Investigating the capacity of AI tools to   (1) DALL-E-2, Midjournet and Blue Willow showed a
 intelligence tools in cosmetic   Medicine  generate realistic images pertinent to cosmetic   higher representation of females, light skin tones, and
 surgery: a study on rhinoplasty,   surgery  with a BMI < 20
 facelifts, and blepharoplasty              (2) AI tools could enhance patient information but must
 procedures                                 be integrated ethically to ensure comprehensive
                                            representation and maintain medical standards
 Hand surgery  Ozkaya   Evaluation of an artificial   2022 European Journal of  (1) Determine the diagnostic performance of ML to  (1) ML demonstrated 76% sensitivity, 92% specificity,
 [46]
 et al.  intelligence system for diagnosing   Trauma and   detect scaphoid fractures on anteroposterior wrist  an AUC of 0.840, a Youden index of 0.680, and an F-
 scaphoid fracture on direct   Emergency Surgery radiographs  score of 0.826 for detecting scaphoid fractures
 radiography                                (2) The experienced orthopedic specialist had the
                                            highest diagnostic performance based on AUC, while ML
                                            performance was comparable to that of a less
                                            experienced orthopedic specialist and superior to the ED
                                            physician
 [47]
 Oeding et al.  Diagnostic performance of artificial  2024 The Journal of   (1) Determine the diagnostic efficacy of AI models   (1) AI models exhibited strong diagnostic performance,
 intelligence for detection of   Hand Surgery  for detecting scaphoid and distal radius fractures   with AUROC values ranging from 0.77 to 0.96 for
 scaphoid and distal radius   (2) Compare the efficacy to human clinical experts  scaphoid fractures and 0.90 to 0.99 for distal radius
 fractures: a systematic review             fractures. Accuracy ranged from 72.0% to 90.3% for
                                            scaphoid fractures and 89.0% to 98.0% for distal radius
                                            fractures
                                            (2) Compared to clinical experts, 92.9% of the studies
                                            found AI models to have comparable or better
                                            performance. AI models generally showed poorer
                                            performance on occult scaphoid fractures, though
                                            models specifically trained for these types of fractures
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