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Related Concept Videos

Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

248
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
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Biological Influences on Intelligence01:30

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Intelligence is often thought to be linked to brain size, but the relationship is more complex than that. While brain size does correlate modestly with some abilities, like verbal skills, the connection is weaker for others, such as spatial reasoning. Other factors, like brain structure, also play crucial roles. For instance, despite Einstein's smaller-than-average brain, his parietal cortex, which is involved in spatial reasoning, was 15% wider, suggesting that neural density might matter...
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Updated: May 16, 2025

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Cephalometric tracing: comparing artificial intelligence and augmented intelligence on online platforms.

E A Gallardo-Lopez1, Lmya Moreira1, M H Cruz1

  • 1Department of Stomatology, School of Dentistry, University of Sao Paulo, Sao Paulo 05508-000, Brazil.

Dento Maxillo Facial Radiology
|May 15, 2025
PubMed
Summary
This summary is machine-generated.

AI cephalometric analysis shows variability based on user adjustments, impacting orthodontic diagnosis and treatment planning. Augmented intelligence integration is recommended for improved accuracy and reliability in clinical practice.

Keywords:
artificial intelligencecephalometryorthodonticsradiographysemi-autonomous AI systemsupervised machine learning

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Area of Science:

  • Dentistry
  • Orthodontics
  • Artificial Intelligence

Background:

  • Cephalometric analysis is crucial for orthodontic diagnosis and treatment planning.
  • AI-powered platforms offer automated cephalometric analysis, but their reliability with user modifications requires evaluation.

Purpose of the Study:

  • To assess the accuracy and variability of AI-driven cephalometric analyses from RadioCef®, EasyCeph®, and WebCeph® platforms.
  • To investigate the impact of examiner modifications on AI cephalometric analysis results.

Main Methods:

  • Seventy cephalometric radiographs were analyzed using AI on three platforms.
  • Four examiners with varying expertise reviewed and corrected landmark placements.
  • Statistical analysis, including repeated measures ANOVA and ICC, was used to evaluate differences and agreement.

Main Results:

  • High landmark modification rates (>90%) were observed across platforms, with more experienced examiners making more changes.
  • Statistically significant differences were found in key cephalometric angles (SNA, SNB, ANB, SN-GoGn, FMIA, FMA, IMPA) between automated and semi-automated analyses.
  • Intra-observer agreement ranged from poor to perfect, while inter-observer agreement was good to excellent.

Conclusions:

  • Fully automated cephalometric analysis exhibits variability influenced by examiner input.
  • These variations pose challenges for orthodontists in diagnosis and treatment planning.
  • Augmented intelligence, combining AI with human expertise, is suggested for reliable cephalometric analysis.