A new study in Frontiers in Pediatrics has used machine learning to look at a large medical claims database to determine the prevalence, gender demographics, and costs for individuals living with ME/CFS. Since ME/CFS is such a heterogeneous disease, there is a lack of diagnostic testing and confusion about how to code the disease, making it difficult for an individual to be diagnosed. This also makes it problematic to estimate other aspects of the disease, such as prevalence, but this study offers a new approach to this problem by using machine learning to look at characteristics of patients who have been given a diagnosis code for ME or CFS to makes these estimates.

Continue reading “Frontiers: Machine Learning to Estimate Prevalence, Demographics, and Costs of ME/CFS” →

The ME/CFS Collaborative Research Centers (CRCs) have a new Website!  The site that just went live aims at informing the community about the ongoing research at the three CRCs, or ME/CFS Research Network (MECFSnet), and was developed by the Data Management Coordinating Center (DMCC). There are features and information about the research projects happening at Columbia University, Cornell University, and The Jackson Laboratory. We hope that it will be updated frequently and welcome the feedback of the ME/CFS community.

Click here to visit the new MECFSnet website!