Automated tools for identifying the causes of anaemia in general practices are particularly advantageous for patients who do not fit the typical profile.

Bauke Arjen de BoerTatum T van LaarFirmin CandidoKarlijn J van StralenAnne Margreet de Jong

Published in: Annals of clinical biochemistry (2024)

The percentage patients in which an underlying cause of anaemia was found increased 34 and 46 percentage points in males and females, respectively, when GPs were supported by CDS-anaemia compared to GPs who were not supported by CDS-anaemia. The highest increase in percentage points when CDS-anaemia was used, was found in younger- and middle-aged males and mild or moderate anaemia.

Keyphrases

iron deficiency
quantum dots
middle aged
healthcare
newly diagnosed
ejection fraction
primary care
machine learning
prognostic factors
high intensity
deep learning
high throughput
single cell