Wesam Alramadeen, Yu Ding, et al.
IISE Transactions on Healthcare Systems Engineering
Patient Electronic Health Records (EHRs) typically contain a substantial amount of data, which can lead to information overload for clinicians, especially in high-throughput fields like radiology. Thus, it would be beneficial to have a mechanism for summarizing the most clinically relevant patient information pertinent to the needs of clinicians. This study presents a novel approach for the curation of clinician EHR data preference information towards the ultimate goal of providing robust EHR summarization. Clinicians first provide a list of data items of interest across multiple EHR categories. Since this data is manually dictated, it has limited coverage and may not cover all the important terms relevant to a concept. To address this problem, we have developed a knowledge-driven semantic concept expansion approach by leveraging rich biomedical knowledge from the UMLS. The approach expands 1094 seed concepts to 22,325 concepts with 92.69% of the expanded concepts identified as relevant by clinicians.
Wesam Alramadeen, Yu Ding, et al.
IISE Transactions on Healthcare Systems Engineering
John M. Prager, Jennifer J. Liang, et al.
AMIA Joint Summits on Translational Science 2017
Mattia C.F. Prosperi, Andre Altmann, et al.
Antiviral Therapy
Heather Fraser, Edgar L Mounib, et al.
Healthcare financial management : journal of the Healthcare Financial Management Association