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Real-Time, Objective Assessment of Facial Paralysis Using a Mobile Tool (FaceADE): Feasibility Case-Control Study.

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Related Experiment Video

Updated: Jun 21, 2025

Single-stage Dynamic Reanimation of the Smile in Irreversible Facial Paralysis by Free Functional Muscle Transfer
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Artificial Intelligence in Facial Plastics and Reconstructive Surgery.

Ki Wan Park1, Mohamed Diop1, Sierra Hewett Willens1

  • 1Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine, 801 Welch Road, Palo Alto, CA 94305, USA.

Otolaryngologic Clinics of North America
|July 6, 2024
PubMed
Summary

Artificial intelligence (AI) offers objective tools to enhance facial plastic and reconstructive surgery (FPRS) for diagnosis, planning, and evaluation. Challenges like bias and validation need addressing for clinical integration of AI in FPRS.

Keywords:
Artificial intelligenceDeep learningFacial plastic and reconstructive surgeryMachine learning

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Area of Science:

  • Medical technology
  • Computer science
  • Plastic surgery

Background:

  • Facial plastic and reconstructive surgery (FPRS) currently faces subjective limitations in patient evaluation.
  • Advancements in artificial intelligence (AI), including computer vision and large language models, present opportunities to overcome these limitations.

Purpose of the Study:

  • To discuss the impact of AI on FPRS.
  • To explore current and emerging AI technologies for clinical application in FPRS.
  • To highlight the future potential of AI in the field.

Main Methods:

  • Review of current and emerging AI technologies relevant to FPRS.
  • Discussion of AI's role in diagnostic accuracy, surgical planning, and post-operative evaluation.
  • Analysis of challenges to AI integration in clinical settings.

Main Results:

  • AI technologies can provide objective tools for patient evaluation in aesthetic surgery.
  • AI can enhance diagnostic accuracy, surgical planning, and post-operative assessments in FPRS.
  • Significant challenges remain, including algorithmic bias, ethical considerations, and the need for validation.

Conclusions:

  • AI holds substantial potential to revolutionize FPRS by introducing objective assessment tools.
  • Clinical integration of AI in FPRS requires addressing ethical concerns and ensuring robust validation.
  • The future of FPRS will likely involve significant AI-driven advancements.