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View article: Community-acquired pneumonia identification from electronic health records in the absence of a gold standard: A Bayesian latent class analysis
Community-acquired pneumonia identification from electronic health records in the absence of a gold standard: A Bayesian latent class analysis Open
Community-acquired pneumonia (CAP) is common and a significant cause of mortality. However, CAP surveillance commonly relies on diagnostic codes from electronic health records (EHRs), with imperfect accuracy. We used Bayesian latent class …
View article: Community-acquired pneumonia identification from electronic health records in the absence of a gold standard: a Bayesian latent class analysis
Community-acquired pneumonia identification from electronic health records in the absence of a gold standard: a Bayesian latent class analysis Open
Background Community-acquired pneumonia (CAP) is common and a significant cause of mortality. However, CAP surveillance commonly relies on diagnostic codes from electronic health records (EHRs), whose accuracy is imperfect. Methods We used…
View article: Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections
Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections Open
Predicting AMR in bloodstream infections is challenging for both clinicians and models. Despite modest performance, machine learning models could still increase the proportion of patients receiving active empirical treatment by up to 9% ov…
View article: Interplay between C-reactive protein responses and antibiotic prescribing in suspected bloodstream infections
Interplay between C-reactive protein responses and antibiotic prescribing in suspected bloodstream infections Open
Serial measurements of C-reactive protein (CRP) are often taken in hospitals to assess recovery from infection, but their utility remains debated. We examined antibiotic prescribing patterns and their association with CRP centile changes i…
View article: Machine learning to predict antibiotic susceptibility in Enterobacterales bloodstream infections compared to clinician prescribing
Machine learning to predict antibiotic susceptibility in Enterobacterales bloodstream infections compared to clinician prescribing Open
Background Patients with Gram-negative bloodstream infections are at risk of serious adverse outcomes without active treatment, but identifying who has antimicrobial resistance (AMR) to target empirical treatment is challenging. Methods We…
View article: Improving patient flow through hospitals with machine learning based discharge prediction
Improving patient flow through hospitals with machine learning based discharge prediction Open
Accurate predictions of hospital discharge events could help improve patient flow through hospitals and the efficiency of care delivery. However, the potential of integrating machine learning with diverse electronic health records (EHR) da…