Electronic health records (EHR) contain a lot of valuable information about individual
patients and the whole population. Besides structured data, unstructured data in EHRs can …

Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …

Early prediction of patient outcomes is important for targeting preventive care. This protocol
describes a practical workflow for developing deep-learning risk models that can predict …

Objective To determine the effects of using unstructured clinical text in machine learning
(ML) for prediction, early detection, and identification of sepsis. Materials and methods …

Objective This systematic review aims to assess how information from unstructured text is
used to develop and validate clinical prognostic prediction models. We summarize the …

Background The promise of digital health is principally dependent on the ability to
electronically capture data that can be analyzed to improve decision-making. However, the …

One unintended consequence of the Electronic Health Records (EHR) implementation is the
overuse of content-importing technology, such as copy-and-paste, that creates “bloated” …

Objective To identify and synthesise research on applications of natural language
processing (NLP) for information extraction and retrieval from clinical notes in dentistry …

This paper proposes a novel scheme for the leaker identification that deals with the dynamic
scenario by handling the requests of the users in an online custom. A distribution strategy is …

Clinical prediction models often use structured variables and provide outcomes that are not
readily interpretable by clinicians. Further, free-text medical notes may contain information …