Yufan Guo, Deepika Kakrania, et al.
AAAI 2017
EMR systems are intended to improve patient-centered care management and hospital administrative processing. However, the information stored in EMRs can be disorganized, incomplete, or inconsistent, creating problems at the patient and system level. We present a technology that reconciles inconsistencies between clinical diagnoses and administrative records by analyzing free-text notes, problem lists and recorded diagnoses in real time. A fully integrated pipeline has been developed for efficient, knowledge-driven extraction, normalization, and matching of disease terms among structured and unstructured data, with modular precision of 94-98% on over 1000 patients. This cognitive data review tool improves the path from diagnosis to documentation, facilitating accurate and timely clinical and administrative decision-making.
Yufan Guo, Deepika Kakrania, et al.
AAAI 2017
Tyler Baldwin, Yufan Guo, et al.
AMIA Annual Symposium
Tianran Hu, Anbang Xu, et al.
CHI 2018
Zhe Liu, Anbang Xu, et al.
CHI 2018