Work

Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients

Year: 2019
Type: article
Abstract: Patients admitted to the intensive care unit frequently have anemia and impaired renal function, but often lack historical blood results to contextualize the acuteness of these findings. Using data available within two hours of ICU admission, we developed machine learning models that accurately (AUC 0.86-0.89) classify an individual patient's baseline hemoglobin and creatinine levels. Compared to assuming the baseline to be the same as the admission lab value, machine learning performed significantly better at classifying acute kidney injury regardless of initial creatinine value, and significantly better at predicting baseline hemoglobin value in patients with admission hemoglobin of <10 g/dl.
Language: English
Open Access status: gold
Estimated APC paid: $2,680
OpenAlex ID: W2991141220
FWCI: 2.144
Cites: 51
Cited by: 29
Related to: 10