Artificial Intelligence in Facial Plastic Surgery: A Review of Current Applications, Future Applications, and Ethical Considerations

被引:15
作者
Choi, Elizabeth [1 ]
Leonard, Kyle W. [2 ,5 ]
Jassal, Japnam S. [2 ]
Levin, Albert M. [3 ,4 ]
Ramachandra, Vikas [3 ,4 ]
Jones, Lamont R. [2 ]
机构
[1] Wayne State Univ, Sch Med, Detroit, MI USA
[2] Henry Ford Hosp, Dept Otolaryngol, Detroit, MI USA
[3] Henry Ford Hlth, Dept Publ Hlth Sci, Detroit, MI USA
[4] Ctr Bioinformat, Henry Ford Hlth, Detroit, MI USA
[5] Henry Ford Hosp, Dept Otolaryngol, 2799 W Grand Blvd,K8 W821, Detroit, MI 48202 USA
关键词
artificial intelligence; ethics; machine learning; patient care; PHYSICIAN TIME; AI; CLASSIFICATION;
D O I
10.1055/s-0043-1770160
中图分类号
R61 [外科手术学];
学科分类号
摘要
From virtual chat assistants to self-driving cars, artificial intelligence (AI) is often heralded as the technology that has and will continue to transform this generation. Among widely adopted applications in other industries, its potential use in medicine is being increasingly explored, where the vast amounts of data present in electronic health records and need for continuous improvements in patient care and workflow efficiency present many opportunities for AI implementation. Indeed, AI has already demonstrated capabilities for assisting in tasks such as documentation, image classification, and surgical outcome prediction. More specifically, this technology can be harnessed in facial plastic surgery, where the unique characteristics of the field lends itself well to specific applications. AI is not without its limitations, however, and the further adoption of AI in medicine and facial plastic surgery must necessarily be accompanied by discussion on the ethical implications and proper usage of AI in healthcare. In this article, we review current and potential uses of AI in facial plastic surgery, as well as its ethical ramifications.
引用
收藏
页码:454 / 459
页数:6
相关论文
共 45 条
[1]   Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics [J].
Adhikari, Lasith ;
Ozrazgat-Baslanti, Tezcan ;
Ruppert, Matthew ;
Madushani, R. W. M. A. ;
Paliwal, Srajan ;
Hashemighouchani, Haleh ;
Zheng, Feng ;
Tao, Ming ;
Lopes, Juliano M. ;
Li, Xiaolin ;
Rashidi, Parisa ;
Bihorac, Azra .
PLOS ONE, 2019, 14 (04)
[2]  
AI Medical Documentation for Physicians & Hospitals, AUGM
[3]   A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis [J].
Baker, Adam ;
Perov, Yura ;
Middleton, Katherine ;
Baxter, Janie ;
Mullarkey, Daniel ;
Sangar, Davinder ;
Butt, Mobasher ;
DoRosario, Arnold ;
Johri, Saurabh .
FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2020, 3
[4]   Surgical Risk Is Not Linear: Derivation and Validation of a Novel, User-friendly, and Machine-learning-based Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) Calculator [J].
Bertsimas, Dimitris ;
Dunn, Jack ;
Velmahos, George C. ;
Kaafarani, Haytham M. A. .
ANNALS OF SURGERY, 2018, 268 (04) :574-583
[5]   Applied Deep Learning in Plastic Surgery: Classifying Rhinoplasty With a Mobile App [J].
Borsting, Emily ;
DeSimone, Robert ;
Ascha, Mustafa ;
Ascha, Mona .
JOURNAL OF CRANIOFACIAL SURGERY, 2020, 31 (01) :102-106
[6]   Unintended Consequences of Machine Learning in Medicine [J].
Cabitza, Federico ;
Rasoini, Raffaele ;
Gensini, Gian Franco .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2017, 318 (06) :517-518
[7]   A Practical Approach to Artificial Intelligence in Plastic Surgery [J].
Chandawarkar, Akash ;
Chartier, Christian ;
Kanevsky, Jonathan ;
Cress, Phaedra E. .
AESTHETIC SURGERY JOURNAL OPEN FORUM, 2020, 2 (01)
[8]  
deepscribe, AI POWERED MED DOCUM
[9]   Medical students' attitude towards artificial intelligence: a multicentre survey [J].
dos Santos, D. Pinto ;
Giese, D. ;
Brodehl, S. ;
Chon, S. H. ;
Staab, W. ;
Kleinert, R. ;
Maintz, D. ;
Baessler, B. .
EUROPEAN RADIOLOGY, 2019, 29 (04) :1640-1646
[10]   Dermatologist-level classification of skin cancer with deep neural networks [J].
Esteva, Andre ;
Kuprel, Brett ;
Novoa, Roberto A. ;
Ko, Justin ;
Swetter, Susan M. ;
Blau, Helen M. ;
Thrun, Sebastian .
NATURE, 2017, 542 (7639) :115-+