Facial Expression Recognition With Machine Learning and Assessment of Distress in Patients With Cancer.

Objectives: To estimate the effectiveness of combining facial expression recognition and machine learning for better detection of distress.

Sample & Setting: 232 patients with cancer in Sichuan University West China Hospital in Chengdu, China.

Methods & Variables: The Distress Thermometer (DT) and Hospital Anxiety and Depression Scale (HADS) were used as instruments.