ArticleJournal of medical Internet research2022
How Can Research on Artificial Empathy Be Enhanced by Applying Deepfakes?
Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Digital transformation of mental health therapy by integrating digitalized cognitive behavioral therapy and eye movement desensitization and reprocessing.Medical & biological engineering & computing · 2025Review
- The role of metaverse on sexual health of people with disabilities: narrative review.International journal of impotence research · 2024Review
- Possible Health Benefits and Risks of DeepFake Videos: A Qualitative Study in Nursing Students.Nursing reports (Pavia, Italy) · 2024Article
- Refining CycleGAN with attention mechanisms and age-Aware training for realistic Deepfakes.Heliyon · 2024Article
- A deepfake-based study on facial expressiveness and social outcomes.Scientific reports · 2024Article
- Article
- Prediction of self-efficacy in recognizing deepfakes based on personality traits .F1000Research · 2022Article
- Artificial intelligence technologies and compassion in healthcare: A systematic scoping review.Frontiers in psychology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
We propose the idea of using an open data set of doctor-patient interactions to develop artificial empathy based on facial emotion recognition. Facial emotion recognition allows a doctor to analyze patients' emotions, so that they can reach out to their patients through empathic care. However, face recognition data sets are often difficult to acquire; many researchers struggle with small samples of face recognition data sets. Further, sharing medical images or videos has not been possible, as this approach may violate patient privacy. The use of deepfake technology is a promising approach to deidentifying video recordings of patients' clinical encounters. Such technology can revolutionize the implementation of facial emotion recognition by replacing a patient's face in an image or video with an unrecognizable face-one with a facial expression that is similar to that of the original. This technology will further enhance the potential use of artificial empathy in helping doctors provide empathic care to achieve good doctor-patient therapeutic relationships, and this may result in better patient satisfaction and adherence to treatment.
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Registered trials
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