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Exploring the Practical Applications of Artificial Intelligence, Deep Learning, and Machine Learning in Maxillofacial

Ladislav Czako1, Barbora Sufliarsky1, Kristian Simko1

  • 1Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava and University Hospital, Ruzinovska 6, 826 06 Bratislava, Slovakia.

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Artificial intelligence (AI) and machine learning (ML) are increasingly used in maxillofacial surgery for diagnosis and treatment planning. This review highlights their growing significance and applications in enhancing patient care and surgical outcomes.

Keywords:
artificial intelligencedeep learningevidence–based practicemachine learningmaxillofacial surgery

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Area of Science:

  • Maxillofacial Surgery
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning

Background:

  • Artificial intelligence (AI), deep learning (DL), and machine learning (ML) systems mimic human intelligence, offering advancements in medical diagnostics and planning.
  • These technologies have shown increasing popularity and applicability in maxillofacial surgery over recent decades.

Purpose of the Study:

  • To review the applicability and significance of AI, DL, and ML in maxillofacial surgery.
  • To highlight the current and potential uses of these technologies in the field.

Main Methods:

  • A literature review of original English-language papers on AI, DL, or ML in maxillofacial surgery.
  • Searches conducted on PubMed, Scopus, and Web of Science up to December 31, 2023.
  • Screening of 324 selected publications from 1992 to 2023.

Main Results:

  • A continuous increase in publications related to AI and ML in maxillofacial surgery from 1992 to 2023 (R² = 0.9295).
  • Significant increase in publications when including terms like "planning in maxillofacial surgery" (7535 total).
  • AI and ML are utilized for diagnosis, treatment planning, and outcome assessment in various subfields, including oncology, aesthetics, and orthognathic surgery.

Conclusions:

  • Current applications of AI and ML in maxillofacial surgery primarily focus on digital diagnostics (radiology), treatment planning, and evaluating postoperative results.
  • Integration of AI and ML into maxillofacial and robotic surgery is expected to expand their role in surgical planning and success evaluation.
  • The trend indicates a growing reliance on AI and ML for comprehensive evaluation and planning in maxillofacial procedures.