To create a new drug, researchers have to test tens of thousands of compounds to determine how they interact. The technology aims to streamline the initial phase of drug discovery, which involves analyzing how different molecules interact with one another--specifically, scientists need to determine which molecules will bind together and how strongly.
The current study compared self-report symptom data of patients with ME or CFS with those with MS. The self-report data is from the DePaul Symptom Questionnaire, and participants were recruited to take the questionnaire online. Data were analyzed using a machine learning technique called decision trees. Our findings support the use of machine learning to further explore the unique nature of these different chronic diseases.