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Related Concept Videos

Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

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Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
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Muscles for Facial Expressions01:14

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The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
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Artificial Intelligence in Facial Plastic Procedures.

Nuray Bayar Muluk1

  • 1Otorhinolaryngology Department, Faculty of Medicine, Kırıkkale University, Kırıkkale, Turkey.

Clinical Otolaryngology : Official Journal of ENT-UK ; Official Journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
|October 19, 2025
PubMed
Summary
This summary is machine-generated.

Artificial Intelligence (AI) is transforming facial plastic surgery by aiding decision-making, patient engagement, and outcome prediction. Surgeons should collaborate with data scientists to enhance surgical efficiency and patient care.

Keywords:
artificial intelligence (AI)artificial intelligent virtual assistants (AIVA)convolutional neural networksfacial plasticmachine learning (ML)rhinoplastysoftware

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Area of Science:

  • Medical Technology
  • Artificial Intelligence in Surgery
  • Facial Plastic Surgery

Background:

  • Artificial Intelligence (AI) is increasingly integrated into various medical fields.
  • Facial plastic surgery presents unique opportunities for AI application in patient care, education, and research.

Purpose of the Study:

  • To review the current and potential applications of AI in facial plastic surgery.
  • To explore AI's impact on clinical decision-making, patient engagement, and surgical outcomes.

Main Methods:

  • A comprehensive literature search was conducted using major scientific databases (PubMed, Medline, Google Scholar) from 2000 to 2025.
  • Key AI technologies such as machine learning (ML), neural networks (NN), and natural language processing (NLP) were examined.

Main Results:

  • AI aids in detecting facial features for cosmetic rhinoplasty, analyzing post-operative flap viability, and diagnosing rare craniofacial diseases via facial analysis software.
  • AI virtual assistants (AIVA) utilize NLP for patient consultations, and AI assists in assessing outcomes and surgical training.

Conclusions:

  • AI integration in healthcare is advancing pre-operative assessments, prognosis prediction, patient management, and post-operative monitoring.
  • Collaboration between surgeons and data scientists is crucial to optimize AI for enhanced surgical efficiency, improved patient outcomes, and reduced administrative burden.