Data science for infection management & antimicrobial stewardship
|PhD ceremony:||C.F. (Christian) Luz|
|When:||November 22, 2021|
|Supervisor:||prof. dr. B.N.M. (Bhanu) Sinha|
|Co-supervisors:||M.W.N. Nijsten, dr. C. (Corinna) Glasner|
|Where:||Academy building RUG|
|Faculty:||Medical Sciences / UMCG|
Improving infection management and supporting the rational use of antimicrobials through antimicrobial stewardship requires different disciplines to interact in shared clinical decision-making processes. This thesis explores the use of data science to support these processes by leveraging data from routine electronic health records. New approaches to data wrangling, data visualization, and data modelling and prediction were developed and tested for their potential to support clinicians with data insights that can ultimately improve the quality of patient care.