AIMC Topic: Medical Records
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Prediction of emergency department patient disposition based on natural language processing of triage notes.
International journal of medical informatics
Jun 13, 2019
BACKGROUND: Nursing triage documentation is the first free-form text data created at the start of an emergency department (ED) visit. These 1-3 unstructured sentences reflect the clinical impression of an experienced nurse and are key in gauging a pa...
Using natural language processing to extract structured epilepsy data from unstructured clinic letters: development and validation of the ExECT (extraction of epilepsy clinical text) system.
BMJ open
Apr 1, 2019
OBJECTIVE: Routinely collected healthcare data are a powerful research resource but often lack detailed disease-specific information that is collected in clinical free text, for example, clinic letters. We aim to use natural language processing techn...
Statistical outbreak detection by joining medical records and pathogen similarity.
Journal of biomedical informatics
Feb 13, 2019
We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines patient exposures, determined from electronic medical records, and pathogen similarity, determined by...
Learning to Personalize from Practice: A Real World Evidence Approach of Care Plan Personalization based on Differential Patient Behavioral Responses in Care Management Records.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
Recent studies documented the importance of individuality and heterogeneity in care planning. In practice, varying behavioral responses are revealed in patients' care management (CM) records. However, today's care programs are structured around popul...
Toward Automatic Risk Assessment to Support Suicide Prevention.
Crisis
Nov 26, 2018
Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategies being applied, the rate of suicide has not changed substantially over the past decades. Suicide ri...
Machine learning in medicine: Addressing ethical challenges.
PLoS medicine
Nov 6, 2018
Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.
Clinical Named Entity Recognition Using Deep Learning Models.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. ...
The Problems of Realism-Based Ontology Design: a Case Study in Creating Definitions for an Application Ontology for Diabetes Camps.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
A requirement of realism-based ontology design is that classes denote exclusively entities that exist objectively in reality and that their definitions adhere to strict criteria to ensure that the classes are re-usable in other ontologies while prese...
Deep Learning Meets Biomedical Ontologies: Knowledge Embeddings for Epilepsy.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
While biomedical ontologies have traditionally been used to guide the identification of concepts or relations in biomedical data, recent advances in deep learning are able to capture high-quality knowledge from textual data and represent it in graphi...
A pattern learning-based method for temporal expression extraction and normalization from multi-lingual heterogeneous clinical texts.
BMC medical informatics and decision making
Mar 22, 2018
BACKGROUND: Temporal expression extraction and normalization is a fundamental and essential step in clinical text processing and analyzing. Though a variety of commonly used NLP tools are available for medical temporal information extraction, few wor...
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