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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Updated: May 6, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
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Enhancing Craniomaxillofacial Surgeries with Artificial Intelligence Technologies.

Wesley Do1, Niels van Nistelrooij2, Stefaan Bergé1

  • 1Department of Oral & Maxillofacial Surgery, Radboud UMC, Philips van Leydenlaan 25, 6525 EX Nijmegen, The Netherlands.

Oral and Maxillofacial Surgery Clinics of North America
|May 17, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances craniomaxillofacial (CMF) surgery across various subspecialties. This review details AI applications in diagnosis, planning, and treatment, highlighting its transformative potential in CMF surgical procedures.

Keywords:
Artificial intelligenceDigital craniomaxillofacial surgeryFracture detectionPredictive analysisVirtual surgical planningWhole slide imaging

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Area of Science:

  • Craniomaxillofacial (CMF) Surgery
  • Medical Artificial Intelligence (AI)

Background:

  • Artificial intelligence (AI) offers significant potential across multiple craniomaxillofacial (CMF) surgical subspecialties.
  • Core AI tasks like classification, object detection, and segmentation are fundamental to CMF applications.

Purpose of the Study:

  • To provide a comprehensive overview of AI fundamentals and their applications in CMF surgery.
  • To explore the integration and impact of AI in diverse CMF subspecialties and surgical phases.

Main Methods:

  • Review of AI fundamentals, including classification, object detection, and segmentation.
  • Exploration of AI development and integration in dentoalveolar surgery, implantology, traumatology, oncology, craniofacial surgery, and orthognathic/feminization surgery.

Main Results:

  • AI is being integrated into diagnosis, pre-operative planning, intra-operative assistance, post-operative management, and outcome prediction in CMF surgery.
  • AI-driven advancements are noted across various CMF subspecialties, improving surgical workflows and patient care.

Conclusions:

  • AI adoption in CMF surgery is progressing, offering enhanced capabilities from diagnosis to outcome prediction.
  • Challenges such as data limitations, algorithm validation, and clinical integration require ongoing attention for successful AI implementation in CMF surgery.