Medical Research Publications
Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review
This study examines how AI can identify potential medication errors or ADEs in EHRs using several machine learning methods.
Associations of physicians’ prescribing experience, work hours, and workload with prescription errors
This study assessed the associations between a physician workload, successive shifts, and work experience as it relates to making potential medication errors.
Using a Machine Learning System to Identify and Prevent Medication Prescribing Errors: A Clinical and Cost Analysis Evaluation
MedAware’s machine learning algorithms were compared to an existing CDS system to determine clinical relevance alerts to prevent adverse events.
Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting
This study examined the results of MedAware’s technology integrated into an existing EMR in a single medical ward in a tertiary medical center.
Screening for medication errors using an outlier detection system
This study evaluated the accuracy, validity, and clinical usefulness of MedAware’s outlier detection technology to identify medication errors.