Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

Understand

Clinical decision making is challenging because of pathological complexity, as well as large amounts of heterogeneous data generated as part of routine clinical care.

• In recent years, machine learning tools have been developed to aid this process.
• Intensive care unit (ICU) admissions represent the most data dense and time-critical patient care episodes.
• In this context, prediction models may help clinicians determine which patients are most at risk and prioritize care.