[The critique of an artificial intelligence tool in the assessment of peripheral facial paralysis].

Abstract

Peripheral facial palsy (PFP) is an alteration in the functioning of some facial muscles following an injury to the facial nerve. This pathology has functional and aesthetic consequences that impact the quality of life of patients. Their care is essential and begins with an accurate assessment. Currently, scoring scales such as Sunnybrook Facial Grading System (SFGS) or House-Brackmann Grading System (HBGS) are used, based on clinician judgment. However, these evaluation methods can be subject to a certain degree of subjectivity. Recent advances in technology have led to increased interest in artificial intelligence (AI). AI could make it possible to develop an objective, automated and quantitative assessment tool, applicable in a clinical setting. This approach aims to reduce the subjectivity induced by current evaluation. We conducted a retrospective study of 38 patients with moderate-severe to total PFPs. The objective of the study is to identify the benefits and limitations of Emotrics+, a facial metrics tool based on AI, in order to determine whether the tool is applicable in the clinic. This protocol took place at two different time periods (14days and 1year post-PFP) using the SFGS scale and the Emotrics+ software. We evaluated the inter-rater and intra-rater reliability in order to determine the reliability and the reproducibility of the two tools. Then, we established a correlation between the two tools to determine if Emotrics+ followed SFGS's trend. Our currents results do not support the immediate applicability of this software. However, with appropriates adjustments, Emotrics+ has a certain potential.