PRIME Workshop 1: How AI/ML methods can enhance ME/CFS molecular or genetic biomarker discovery
ME/CFS and Long Covid (LC) are chronic and debilitating illnesses whose symptoms often persist years after disease onset. LC occurs after SARS-CoV-2 viral infection and ME/CFS often occurs after other infections. ME/CFS is defined by post-exertional malaise (PEM), the dramatic worsening of symptoms, or new symptoms, after even minor mental or physical exertion. ME/CFS and LC share substantial overlap in symptomatology.
There are no medical interventions that cure ME/CFS and LC. However, data sources including large-scale Biobanks (e.g., UK Biobank, All-of-Us), Electronic Health Records and clinical trials are available to investigate questions regarding diagnosis or disease trajectories, and to generate hypotheses for disease-causal molecular pathways to allow design of possible treatments.
Rigorous AI/ML and statistical methodologies play a central role in answering such questions. The aim of this workshop is to present state-of-the-art quantitative methodologies that have been, or could be, applied in the context of ME/CFS and LC to motivate and empower researchers to take on and apply promising techniques in their own work in this area.
The workshop covers key considerations for valid application of advanced methodologies, explains common mistakes when applying the methods (e.g., model-misspecification in estimation problems, lack of held-out data for final evaluation of prediction model, lack of uncertainty quantification), and presents exemplar biomedical results.