Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient–nurse verbal communications in home healthcare settings?

Identifying health problems in audio-recorded patient-nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning classifiers for identifying problems requires resource-intensive human annotation.