Early identification of patients at risk for iron-deficiency anemia using deep learning techniques.

Nelly Estefanie Garduno-RappYee Seng NgJenny L WeonSameh N SalehChristoph U LehmanChenlu TianAndrew Quinn

Published in: American journal of clinical pathology (2024)

Our results showcase the feasibility of employing deep learning techniques for early prediction of IDA in the outpatient setting based on sequences of laboratory data, offering a substantial lead time for clinical intervention.

Keyphrases

deep learning
iron deficiency
end stage renal disease
chronic kidney disease
ejection fraction
newly diagnosed
randomized controlled trial
artificial intelligence
machine learning
convolutional neural network
prognostic factors
peritoneal dialysis
electronic health record
big data
data analysis
patient reported