Mandibular Gender Dimorphism: The Utility of Artificial Intelligence and Statistical Shape Modeling in Skeletal Facial Analysis.
Jess D RamesSara M HusseinAbdallah A ShehabAlexandre M PazelliVictoria A SearsAdam J WentworthJonathan M MorrisBasel A SharafPublished in: Aesthetic plastic surgery (2024)
This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 . Bullet points about the importance of this work: Advancing Anthropometric Assessment: Statistical shape modeling (SSM) offers a cutting-edge approach to visualizing gender-specific skeletal anatomic differences for aesthetic and gender-affirming facial surgery. Expediting Comparative Analysis: The workflow established in this paper streamlines the evaluative process, enabling rapid morphologic comparisons between populations. Patient-Centered Care: This study establishes a foundation for the development of SSMs in individualized operative planning.
Keyphrases
- artificial intelligence
- machine learning
- mental health
- big data
- deep learning
- healthcare
- minimally invasive
- palliative care
- coronary artery bypass
- soft tissue
- pain management
- health information
- acute coronary syndrome
- chronic pain
- living cells
- loop mediated isothermal amplification
- atrial fibrillation
- health insurance
- surgical site infection