A Synthetic Data Generation System For Myalgic Encephalomyelitis/chronic Fatigue Syndrome Questionnaires

This article discusses the use of artificial intelligence and machine-learning-based models to better understand Myalgic Encephalomyelitis or chronic fatigue syndrome (ME/CFS). A synthetic data generator was used to analyze 2522 patients diagnosed with ME/CFS and their answers to questionnaires related to the symptoms of this complex disease were used as training datasets. Deep learning algorithms were used to create models with high accuracy and the final model requires SF-36 responses and returns responses from HAD, SCL-90R, FIS8, FIS40, and PSQI questionnaires.