23 citations · 44 across the 3 of their papers we have counts for
3 papers
The Consequences of the Framing of Machine Learning Risk Prediction Models: Evaluation of Sepsis in General Wards
Simon Meyer Lauritsen, Bo Thiesson, Marianne Johansson Jørgensen +4
Objectives: To evaluate the consequences of the framing of machine learning risk prediction models. We evaluate how framing affects model performance and model learning in four dif…
Explainable artificial intelligence model to predict acute critical illness from electronic health records
Simon Meyer Lauritsen, Mads Kristensen, Mathias Vassard Olsen +5
We developed an explainable artificial intelligence (AI) early warning score (xAI-EWS) system for early detection of acute critical illness. While maintaining a high predictive per…
Early detection of sepsis utilizing deep learning on electronic health record event sequences
Simon Meyer Lauritsen, Mads Ellersgaard Kalør, Emil Lund Kongsgaard +4
The timeliness of detection of a sepsis event in progress is a crucial factor in the outcome for the patient. Machine learning models built from data in electronic health records c…