Facial Plast Surg 2023; 39(05): 508-511
DOI: 10.1055/s-0043-1769805
Original Article

Deep Learning for the Assessment of Facial Nerve Palsy: Opportunities and Challenges

Kieran Boochoon
1   Department of Otolaryngology – Head and Neck Surgery, University of Nebraska Medical Center, Omaha, Nebraska
,
Ali Mottaghi
2   Department of Electrical Engineering, Stanford University, Stanford, California
,
Aya Aziz
3   Department of Human Biology, Stanford University, Stanford, California
,
Jon-Paul Pepper
4   Department of Otolaryngology – Head and Neck Surgery, Stanford University School of Medicine, Stanford, California
› Author Affiliations

Abstract

Automated evaluation of facial palsy using machine learning offers a promising solution to the limitations of current assessment methods, which can be time-consuming, labor-intensive, and subject to clinician bias. Deep learning-driven systems have the potential to rapidly triage patients with varying levels of palsy severity and accurately track recovery over time. However, developing a clinically usable tool faces several challenges, such as data quality, inherent biases in machine learning algorithms, and explainability of decision-making processes. The development of the eFACE scale and its associated software has improved clinician scoring of facial palsy. Additionally, Emotrics is a semiautomated tool that provides quantitative data of facial landmarks on patient photographs. The ideal artificial intelligence (AI)-enabled system would analyze patient videos in real time, extracting anatomic landmark data to quantify symmetry and movement, and estimate clinical eFACE scores. This would not replace clinician eFACE scoring but would offer a rapid automated estimate of both anatomic data, similar to Emotrics, and clinical severity, similar to the eFACE. This review explores the current state of facial palsy assessment, recent advancements in AI, and the opportunities and challenges in developing an AI-driven solution.



Publication History

Article published online:
08 June 2023

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