AIMC Topic: Electronic Health Records

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Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.

BMC medical informatics and decision making
BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, em...

Is it possible to automatically assess pretreatment digital rectal examination documentation using natural language processing? A single-centre retrospective study.

BMJ open
OBJECTIVES: To develop and test a method for automatic assessment of a quality metric, provider-documented pretreatment digital rectal examination (DRE), using the outputs of a natural language processing (NLP) framework.

TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records.

Computers in biology and medicine
BACKGROUND: Insulin resistance is an early-stage deterioration of Type 2 diabetes. Identification and quantification of insulin resistance requires specific blood tests; however, the triglyceride-glucose (TyG) index can provide a surrogate assessment...

Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom.

BMC medicine
Big data, coupled with the use of advanced analytical approaches, such as artificial intelligence (AI), have the potential to improve medical outcomes and population health. Data that are routinely generated from, for example, electronic medical reco...

Performance of a Natural Language Processing Method to Extract Stone Composition From the Electronic Health Record.

Urology
OBJECTIVES: To demonstrate the utility of a natural language processing (NLP) algorithm for mining kidney stone composition in a large-scale electronic health records (EHR) repository.

A disease inference method based on symptom extraction and bidirectional Long Short Term Memory networks.

Methods (San Diego, Calif.)
The wide applications of automatic disease inference in many medical fields improve the efficiency of medical treatments. Many efforts have been made to predict patients' future health conditions according to their full clinical texts, clinical measu...

Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings.

Nature communications
In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform ...

Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records.

BMC medical informatics and decision making
BACKGROUND: Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary ...

Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression.

International journal of medical informatics
OBJECTIVE: Electronic health record (EHR) systems contain structured data (such as diagnostic codes) and unstructured data (clinical documentation). Clinical insights can be derived from analyzing both. The use of natural language processing (NLP) al...