Abstract
Abstract
The field of psychiatry has been limited in its use of patient videos for educational purposes because essential facial information must be obscured to protect patient privacy, confidentiality, and dignity. This article calls attention to emerging technologies for deidentification of patients in video recordings while still preserving facial expression. Fully anonymized videos could be used to augment the education of psychiatric residents and for continuing education of the psychiatric workforce. This article suggests projects that deidentification technology could make possible; it also outlines some complex problems that would need to be addressed before the field could use this potentially transformative technology.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Psychiatry and Mental health
Reference6 articles.
1. Private face image generation method based on deidentification in low light;Comput Intell Neurosci,2022
2. Disentangled representation learning for multiple attributes preserving face deidentification;IEEE Trans Neural Netw Learn Syst,2020
3. E-library of authentic patient videos improves medical students' mental status examination;Acad Psychiatry,2020
4. Enhanced embedded AutoEncoders: an attribute-preserving face de-identification framework;IEEE Internet Things J,2023
5. AI in health and medicine;Nat Med,2022