AI in plastic surgery: customizing care for each patient

被引:3
作者
Brenac, Camille [1 ,2 ]
Fazilat, Alexander Z. [1 ]
Fallah, Mahsa [1 ]
Kawamoto-Duran, Danae [1 ]
Sunwoo, Parker S. [1 ]
Longaker, Michael T. [1 ,3 ]
Wan, Derrick C. [1 ]
Guo, Jason L. [1 ,3 ]
机构
[1] Stanford Univ, Dept Surg, Div Plast & Reconstruct Surg, Hagey Lab Pediat Regenerat Med,Sch Med, 257 Campus Dr, Stanford, CA 94305 USA
[2] Hosp Civils Lyon, Croix Rousse Hosp, Dept Plast Reconstruct & Aesthet Surg, F-69004 Lyon, France
[3] Stanford Univ, Inst Stem Cell Biol & Regenerat Med, Stanford, CA 94305 USA
来源
ARTIFICIAL INTELLIGENCE SURGERY | 2024年 / 4卷 / 04期
关键词
Plastic surgery; machine learning; artificial intelligence; algorithms; ARTIFICIAL-INTELLIGENCE; CANCER; IMPACT;
D O I
10.20517/ais.2024.49
中图分类号
R61 [外科手术学];
学科分类号
摘要
Artificial intelligence (AI) and machine learning (ML) involve the usage of complex algorithms to identify patterns, predict future outcomes, generate new data, and perform other tasks that typically require human intelligence. AI tools have been progressively adopted by multiple disciplines of surgery, enabling increasingly patient-specific care, as well as more precise surgical modeling and assessment. For instance, AI tools such as ChatGPT have been applied to enhance both patient educational materials and patient-surgeon communication. Additionally, AI tools have helped support pre- and postoperative assessment in a diverse set of procedures, including breast reconstructions, facial surgeries, hand surgeries, wound healing operations, and burn surgeries. Further, ML- supported 3D modeling has now been utilized for patient-specific surgical planning and may also be combined with 3D printing technologies to generate patient-customized, implantable constructs. Ultimately, the advent of AI and its intersection with surgical practice have demonstrated immense potential to transform patient care by making multiple facets of the surgical process more efficient, precise, and patient-specific.
引用
收藏
页码:296 / 315
页数:20
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