Objective To describe the reusable transformation process of electronic health records
(EHR), claims, and prescriptions data into Observational Medical Outcome Partnership …

Background In the era of big data, the intensive care unit (ICU) is likely to benefit from real-
time computer analysis and modeling based on close patient monitoring and electronic …

Objective Health data standardized to a common data model (CDM) simplifies and facilitates
research. This study examines the factors that make standardizing observational health data …

Background Diabetes mellitus (DM) is an important public health concern in Singapore and
places a massive burden on health care spending. Tackling chronic diseases such as DM …

Common data models standardize the structures and semantics of health datasets, enabling
reproducibility and large-scale studies that leverage the data from multiple locations and …

Background Electronic health records (EHRs, such as those created by an anesthesia
management system) generate a large amount of data that can notably be reused for clinical …

Background The identification of patient cohorts for recruiting patients into clinical trials
requires an evaluation of study-specific inclusion and exclusion criteria. These criteria are …

Background The increasing availability of molecular and clinical data of cancer patients
combined with novel machine learning techniques has the potential to enhance clinical …

Objective Accessing medical data from multiple institutions is difficult owing to the
interinstitutional diversity of vocabularies. Standardization schemes, such as the common …

There has been significant interest in big data analysis and artificial intelligence (AI) in
medicine. Ever-increasing medical data and advanced computing power have enabled the …