An Explainable Artificial Intelligence Model Proposed for the Prediction of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and the Identification of Distinctive Metabolites.

Fatma Hilal Yagın Abedalrhman Alkhateeb Ali Raza Nagwan Abdel Samee Noha F Mahmoud Cemil Çolak Burak Yagin

Published in: Diagnostics (Basel, Switzerland) (2023)

The proposed model accurately classifies ME/CFS patients based on the selected biomarker candidate metabolites. It offers a clear interpretation of risk estimation for ME/CFS, aiding physicians in comprehending the significance of key metabolomic features within the model.

Keyphrases

artificial intelligence
end stage renal disease
machine learning
big data
ms ms
primary care
deep learning
ejection fraction
chronic kidney disease
newly diagnosed
peritoneal dialysis
depressive symptoms
physical activity
case report