REFERENCES
1. Hirigoyen MB, Urken ML, Weinberg H. Free flap monitoring: a review of current practice. Microsurgery. 1995;16:723-6.
2. Salgado CJ, Moran SL, Mardini S. Flap monitoring and patient management. Plast Reconstr Surg. 2009;124:e295-302.
3. Hidalgo DA, Disa JJ, Cordeiro PG, Hu QY. A review of 716 consecutive free flaps for oncologic surgical defects: refinement in donor-site selection and technique. Plast Reconstr Surg. 1998;102:722-32.
4. Haddock NT, Lakatta AC, Teotia SS. Categorizing patient selection, outcomes, and indications in a decade of 405 profunda artery perforator flaps. Plast Reconstr Surg. 2024;154:632e-40.
5. Ramesh AN, Kambhampati C, Monson JR, Drew PJ. Artificial intelligence in medicine. Ann R Coll Surg Engl. 2004;86:334-8.
6. Novakovsky G, Dexter N, Libbrecht MW, Wasserman WW, Mostafavi S. Obtaining genetics insights from deep learning via explainable artificial intelligence. Nat Rev Genet. 2023;24:125-37.
7. Johnson KW, Torres Soto J, Glicksberg BS, et al. Artificial intelligence in cardiology. J Am Coll Cardiol. 2018;71:2668-79.
8. Topalovic M, Das N, Burgel PR, et al; Pulmonary Function Study Investigators; Pulmonary Function Study Investigators. Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests. Eur Respir J. 2019;53:1801660.
9. Kurmis AP, Ianunzio JR. Artificial intelligence in orthopedic surgery: evolution, current state and future directions. Arthroplasty. 2022;4:9.
10. Lareyre F, Adam C, Carrier M, Chakfé N, Raffort J. Artificial intelligence for education of vascular surgeons. Eur J Vasc Endovasc Surg. 2020;59:870-1.
11. Kwon DY, Villavisanis DF, Oleru O, et al. Implications for the use of artificial intelligence in plastic surgery research and practice. Plast Reconstr Surg. 2024;153:862e-3.
12. Blum JD, Beiriger J, Villavisanis DF, et al. Machine learning in metopic craniosynostosis: does phenotypic severity predict long-term esthetic outcome? J Craniofac Surg. 2023;34:58-64.
13. Villavisanis DF, Khandelwal P, Zapatero ZD, et al. Craniofacial soft-tissue anthropomorphic database with magnetic resonance imaging and unbiased diffeomorphic registration. Plast Reconstr Surg. 2024;153:667-77.
14. Villavisanis DF, Shakir S, Zhao C, et al. Predicting changes in cephalic index following spring-mediated cranioplasty for nonsyndromic sagittal craniosynostosis: a stepwise and machine learning algorithm approach. J Craniofac Surg. 2022;33:2333-8.
15. Ono S, Hayashi H, Ohi H, Ogawa R. Imaging studies for preoperative planning of perforator flaps: an overview. Clin Plast Surg. 2017;44:21-30.
16. Nahabedian MY, Momen B, Galdino G, Manson PN. Breast reconstruction with the free TRAM or DIEP flap: patient selection, choice of flap, and outcome. Plast Reconstr Surg. 2002;110:466-75.
17. Cevik J, Seth I, Hunter-Smith DJ, Rozen WM. A history of innovation: tracing the evolution of imaging modalities for the preoperative planning of microsurgical breast reconstruction. J Clin Med. 2023;12:5246.
18. Smit JM, Klein S, Werker PM. An overview of methods for vascular mapping in the planning of free flaps. J Plast Reconstr Aesthet Surg. 2010;63:e674-82.
19. Thimmappa ND. MRA for preoperative planning and postoperative management of perforator flap surgeries: a review. J Magn Reson Imaging. 2024;59:797-811.
20. Lim B, Cevik J, Seth I, et al. Evaluating artificial intelligence’s role in teaching the reporting and interpretation of computed tomographic angiography for preoperative planning of the deep inferior epigastric artery perforator flap. JPRAS Open. 2024;40:273-85.
21. Bassani S, Eccher A, Molteni G. Harnessing the power of artificial intelligence: revolutionizing free flaps monitoring in head and neck tumor treatment. Crit Rev Oncog. 2023;28:25-30.
22. Asaad M, Lu SC, Hassan AM, et al. The use of machine learning for predicting complications of free-flap head and neck reconstruction. Ann Surg Oncol. 2023;30:2343-52.
23. Formeister EJ, Baum R, Knott PD, et al. Machine learning for predicting complications in head and neck microvascular free tissue transfer. Laryngoscope. 2020;130:E843-9.
24. Moosa S, Dydynsky R. The role of artificial intelligence in predicting flap outcomes in plastic surgery: protocol of a systematic review. URNCST J. 2022;6:1-8.
25. Li K, Zhang Z, Nicoli F, et al. Application of indocyanine green in flap surgery: a systematic review. J Reconstr Microsurg. 2018;34:77-86.
26. Singaravelu A, Dalli J, Potter S, Cahill RA. Artificial intelligence for optimum tissue excision with indocyanine green fluorescence angiography for flap reconstructions: proof of concept. JPRAS Open. 2024;41:389-93.
27. Atkinson CJ, Seth I, Xie Y, et al. Artificial intelligence language model performance for rapid intraoperative queries in plastic surgery: ChatGPT and the deep inferior epigastric perforator flap. J Clin Med. 2024;13:900.
28. Battaglia S, Badiali G, Cercenelli L, et al. Combination of CAD/CAM and augmented reality in free fibula bone harvest. Plast Reconstr Surg Glob Open. 2019;7:e2510.
29. Cercenelli L, Babini F, Badiali G, et al. Augmented reality to assist skin paddle harvesting in osteomyocutaneous fibular flap reconstructive surgery: a pilot evaluation on a 3D-printed leg phantom. Front Oncol. 2021;11:804748.
30. Tang Y, Guo Q, Li X, Huang Y, Kuang W, Luo L. Augmented reality-assisted systematic mapping of anterolateral thigh perforators. BMC Musculoskelet Disord. 2022;23:1047.
31. Falola RA, Lombana NF, Rodriguez-Unda NA, et al. Augmented reality microsurgery: proof of concept for a novel approach to microsurgical field visualization in plastic surgery. Plast Reconstr Surg. 2024;153:650e-5.
32. Selber JC, Angel Soto-Miranda M, Liu J, Robb G. The survival curve: factors impacting the outcome of free flap take-backs. Plast Reconstr Surg. 2012;130:105-13.
33. Kim J, Lee SM, Kim DE, et al. Development of an automated free flap monitoring system based on artificial intelligence. JAMA Netw Open. 2024;7:e2424299.
34. O’Neill AC, Yang D, Roy M, Sebastiampillai S, Hofer SOP, Xu W. Development and evaluation of a machine learning prediction model for flap failure in microvascular breast reconstruction. Ann Surg Oncol. 2020;27:3466-75.
