AIMC Topic: Natural Language Processing

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Coding and classifying GP data: the POLAR project.

BMJ health & care informatics
BACKGROUND: Data, particularly 'big' data are increasingly being used for research in health. Using data from electronic medical records optimally requires coded data, but not all systems produce coded data.

Data-driven method to enhance craniofacial and oral phenotype vocabularies.

Journal of the American Dental Association (1939)
BACKGROUND: A significant amount of clinical information captured as free-text narratives could be better used for several applications, such as clinical decision support, ontology development, evidence-based practice, and research. The Human Phenoty...

High-throughput multimodal automated phenotyping (MAP) with application to PheWAS.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop ...

Cohort selection for clinical trials: n2c2 2018 shared task track 1.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Track 1 of the 2018 National NLP Clinical Challenges shared tasks focused on identifying which patients in a corpus of longitudinal medical records meet and do not meet identified selection criteria.

Cohort selection for clinical trials using deep learning models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The goal of the 2018 n2c2 shared task on cohort selection for clinical trials (track 1) is to identify which patients meet the selection criteria for clinical trials. Cohort selection is a particularly demanding task to which natural langu...

Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Automated clinical phenotyping is challenging because word-based features quickly turn it into a high-dimensional problem, in which the small, privacy-restricted, training datasets might lead to overfitting. Pretrained embeddings might sol...

NimbleMiner: An Open-Source Nursing-Sensitive Natural Language Processing System Based on Word Embedding.

Computers, informatics, nursing : CIN
This study develops and evaluates an open-source software (called NimbleMiner) that allows clinicians to interact with word embedding models with a goal of creating lexicons of similar terms. As a case study, the system was used to identify similar t...

Transparent Reporting on Research Using Unstructured Electronic Health Record Data to Generate 'Real World' Evidence of Comparative Effectiveness and Safety.

Drug safety
Research that makes secondary use of administrative and clinical healthcare databases is increasingly influential for regulatory, reimbursement, and other healthcare decision-making. Consequently, there are numerous guidance documents on reporting fo...

Real world evidence in cardiovascular medicine: ensuring data validity in electronic health record-based studies.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: With growing availability of digital health data and technology, health-related studies are increasingly augmented or implemented using real world data (RWD). Recent federal initiatives promote the use of RWD to make clinical assertions th...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Prevention science : the official journal of the Society for Prevention Research
Bullying events have frequently been the focus of coverage by news media, including news stories about teens whose death from suicide was attributed to cyberbullying. Previous work has shown that news media coverage is influential to readers in areas...