AIMC Topic: Natural Language Processing

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Increasing the efficiency of trial-patient matching: automated clinical trial eligibility pre-screening for pediatric oncology patients.

BMC medical informatics and decision making
BACKGROUND: Manual eligibility screening (ES) for a clinical trial typically requires a labor-intensive review of patient records that utilizes many resources. Leveraging state-of-the-art natural language processing (NLP) and information extraction (...

SimConcept: a hybrid approach for simplifying composite named entities in biomedical text.

IEEE journal of biomedical and health informatics
One particular challenge in biomedical named entity recognition (NER) and normalization is the identification and resolution of composite named entities, where a single span refers to more than one concept (e.g., BRCA1/2). Previous NER and normalizat...

Incorporating linguistic knowledge for learning distributed word representations.

PloS one
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashio...

Normalization of relative and incomplete temporal expressions in clinical narratives.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To improve the normalization of relative and incomplete temporal expressions (RI-TIMEXes) in clinical narratives.

Multi-focus cluster labeling.

Journal of biomedical informatics
Document collections resulting from searches in the biomedical literature, for instance, in PubMed, are often so large that some organization of the returned information is necessary. Clustering is an efficient tool for organizing search results. To ...

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxe...

Encoding sequential information in semantic space models: comparing holographic reduced representation and random permutation.

Computational intelligence and neuroscience
Circular convolution and random permutation have each been proposed as neurally plausible binding operators capable of encoding sequential information in semantic memory. We perform several controlled comparisons of circular convolution and random pe...

An Evaluation of Patient Safety Event Report Categories Using Unsupervised Topic Modeling.

Methods of information in medicine
OBJECTIVE: Patient safety event data repositories have the potential to dramatically improve safety if analyzed and leveraged appropriately. These safety event reports often consist of both structured data, such as general event type categories, and ...

Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods.

Computer methods and programs in biomedicine
Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of depression are some of the factors preventing people from getting help ...

Building bridges across electronic health record systems through inferred phenotypic topics.

Journal of biomedical informatics
OBJECTIVE: Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution ...