AIMC Topic: Natural Language Processing

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Detection of Medication Mentions and Medication Change Events in Clinical Notes Using Transformer-Based Models.

Studies in health technology and informatics
In this paper, we address the related tasks of medication extraction, event classification, and context classification from clinical text. The data for the tasks were obtained from the National Natural Language Processing (NLP) Clinical Challenges (n...

Extracting Spatio-Temporal Trends in Medical Research Prioritization Through Natural Language Processing of Case Report Abstracts.

Studies in health technology and informatics
Medical research prioritization is an important aspect of decision-making by researchers and relevant stakeholders. The ever-increasing availability of technology and data has opened doors to new discoveries and new questions. This makes it difficult...

Relation Detection to Identify Stroke Assertions from Clinical Notes Using Natural Language Processing.

Studies in health technology and informatics
According to the World Stroke Organization, 12.2 million people world-wide will have their first stroke this year almost half of which will die as a result. Natural Language Processing (NLP) may improve stroke phenotyping; however, existing rule-base...

Using Natural Language Processing to Extract and Classify Symptoms Among Patients with Thyroid Dysfunction.

Studies in health technology and informatics
In the United States, more than 12% of the population will experience thyroid dysfunction. Patient symptoms often reported with thyroid dysfunction include fatigue and weight change. However, little is understood about the relationship between these ...

Advanced Care Planning Content Encoding with Natural Language Processing.

Studies in health technology and informatics
While advanced care planning (ACP) is an essential practice for ensuring patient-centered care, its adoption remains poor and the completeness of its documentation variable. Natural language processing (NLP) approaches hold promise for supporting ACP...

Rule-Based Natural Language Processing Pipeline to Detect Medication-Related Named Entities: Insights for Transfer Learning.

Studies in health technology and informatics
We document the procedure and performance of a rule-based NLP system that, using transfer learning, automatically extracts essential named entities related to drug errors from Japanese free-text incident reports. Subsequently, we used the rule-based ...

Using Natural Language Processing to Predict Risk in Electronic Health Records.

Studies in health technology and informatics
Clinical narratives recording behaviours and emotions of patients are available from EHRs in a forensic psychiatric centre located in Tasmania. This rich data has not been used in risk prediction. Prior work demonstrates natural language processing c...

A Five-Step Workflow to Manually Annotate Unstructured Data into Training Dataset for Natural Language Processing.

Studies in health technology and informatics
Natural Language Processing (NLP) is a powerful technique for extracting valuable information from unstructured electronic health records (EHRs). However, a prerequisite for NLP is the availability of high-quality annotated datasets. To date, there i...

Uncovering Variations in Clinical Notes for NLP Modeling.

Studies in health technology and informatics
Clinical text contains rich patient information and has attracted much research interest in applying Natural Language Processing (NLP) tools to model it. In this study, we quantified and analyzed the textual characteristics of five common clinical no...

Annotation of Opioid Use Disorder Entity Modifiers in Clinical Text.

Studies in health technology and informatics
Natural Language Processing can be used to identify opioid use disorder in patients from clinical text1. We annotate a corpus of clinical text for mentions of concepts associated with unhealthy use of opiates including concept modifiers such as negat...