When it comes to health, a very widespread problem nowadays is mental health, where almost 18% of the world's population suffers from certain mental illnesses. Artificial intelligence (AI) is a concept that evolves strongly and is expected in the near future to bring improvements and help to humans in various fields. The field of mental health is not excluded, so AI can help in the performance of medical services, either by helping the medical staff or patients. In terms of mental health, it has been observed that by recognizing facial expressions, depression, schizophrenia, or other similar conditions can be detected. However, for automatic learning, a very large data set is required for good accuracy. In this paper, we present a facial expression recognition method using only a few training data, which could be used remotely through a mobile or web application.
Keyphrases
- mental health
- artificial intelligence
- big data
- machine learning
- deep learning
- mental illness
- healthcare
- poor prognosis
- end stage renal disease
- electronic health record
- newly diagnosed
- soft tissue
- ejection fraction
- bipolar disorder
- chronic kidney disease
- depressive symptoms
- binding protein
- physical activity
- climate change
- risk assessment
- current status
- long non coding rna
- sleep quality
- patient reported outcomes
- health insurance
- health information
- real time pcr
- loop mediated isothermal amplification