**Background** Automatic facial landmark localization in videos is an important first step in many computer vision applications, including the objective assessment of orofacial function. Convolutional neural networks (CNN) for facial landmarks …
**Importance** Quantitative assessment of facial function is challenging, and subjective grading scales such as House–Brackmann, Sunnybrook, and eFACE have well-recognized limitations. Machine learning (ML) approaches to facial landmark localization …
**Background**
Disease processes causing increased neural compartment pressure may induce transient or permanent neural dysfunction. Surgical decompression can prevent and reverse such nerve damage. Owing to insufficient evidence from controlled …
**Objectives**
Facial palsy causes variable facial disfigurement ranging from subtle asymmetry to crippling deformity. There is no existing standard database to serve as a resource for facial palsy education and research. We present a standardized …
**Importance**
Surgeons have sought to optimize outcomes of smile reanimation surgery by combining inputs from nerve-to-masseter and cross-face nerve grafts. An objective assessment tool could help surgeons evaluate outcomes to determine the optimal …
**Importance**
Quantitative assessment of facial function is difficult, and historic grading scales such as House-Brackmann have well-recognized limitations. The electronic, clinician-graded facial function scale (eFACE) allows rapid regional …
**Background**
Tools to quantify layperson assessments of facial palsy are lacking. In this study, artificial intelligence was applied to develop a proxy for layperson assessments, and compare sensitivity to existing outcome measures. **Methods** …