Drs. Akram Mohammed and Robert L Davis were among six recipients of the Harvey J. Greenberg Research Award, for their paper, “A Machine Learning–Enabled Partially Observable Markov Decision Process Framework for Early Sepsis Prediction,” INFORMS Journal on Computing, published online March 22,2022.
Sepsis can be triggered by the body’s extreme response to an infection and can be life-threatening. Existing sepsis prediction algorithms suffer from high false-alarm rates. The authors present an integrated machine learning (ML) and partially observable Markov decision process framework to address this issue. This approach is calibrated and tested using physiological data collected from bedside monitors. The framework reduces false-alarm rates and improves sepsis prediction accuracy compared to existing ML benchmarks. This is a comprehensive paper with novel contributions to computing and important practical implications. The committee members commend the authors for this excellent work.
Congratulations Drs. Mohammed and Davis!