“…AI was frequently used to predict indications for surgical reconstruction, 17,24,25,30,31,33,43,57,62,64 the likelihood of clinical and technical outcomes (blood loss, 65 swelling‚ 50 response to antibiotics, 40 wound healing, 35,57,66 surgical site infection‚ 62 flap failure‚ 55 and overall survival 64 ), anatomical landmarks for surgical planning (skeletal profiles, 30,31,37 midfacial plane, 29 and perforators 52 ), and measurements of qualitative postoperative success (improvements in aesthetics, 28,29,49,53,56,60 form, 61,63 and function 32,47,54,67 ). The most popular subspecialty was aesthetic and breast surgery (n = 12, 27%), 25–28,47,49,52,55,56,60,61,68 followed by craniofacial surgery (n = 10, 23%), 29–32,37,41,51,54,67,68 nonbreast microsurgery (n = 6, 14%), 39,42,44,45,47,62 burn surgery (n = 5, 11%), 33,40,57,58,64 general plastic surgery (n = 4, 9%), 17,34,48,69 oral and maxillofacial surgery (n = 3, 7%), 43,50,65 wound care (n = 2, 5%), 35,59 and hand surgery (n = 2, 5%). 36,46 AI models were most often in study phases 0 (n = 19) 29–31,33,37–39,41–46,57,…”