AIMC Topic: Natural Language Processing

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The Utility of Clinical Notes for Sexual Minority Health Research.

American journal of preventive medicine
INTRODUCTION: Despite improvements in electronic medical record capability to collect data on sexual orientation, not all healthcare systems have adopted this practice. This can limit the usability of systemwide electronic medical record data for sex...

Multi-Ontology Refined Embeddings (MORE): A hybrid multi-ontology and corpus-based semantic representation model for biomedical concepts.

Journal of biomedical informatics
OBJECTIVE: Currently, a major limitation for natural language processing (NLP) analyses in clinical applications is that concepts are not effectively referenced in various forms across different texts. This paper introduces Multi-Ontology Refined Emb...

Estimating Nonfatal Gunshot Injury Locations With Natural Language Processing and Machine Learning Models.

JAMA network open
IMPORTANCE: Nonfatal gunshot injuries are the most common firearm injury, but where they frequently occur remains unclear owing to data limitations. Natural language processing can be applied to medical text narratives of gunshot injury records to cl...

Development and Validation of a Natural Language Processing Tool to Generate the CONSORT Reporting Checklist for Randomized Clinical Trials.

JAMA network open
IMPORTANCE: Adherence to the Consolidated Standards of Reporting Trials (CONSORT) for randomized clinical trials is associated with improvingquality because inadequate reporting in randomized clinical trials may complicate the interpretation and the ...

Korean clinical entity recognition from diagnosis text using BERT.

BMC medical informatics and decision making
BACKGROUND: While clinical entity recognition mostly aims at electronic health records (EHRs), there are also the demands of dealing with the other type of text data. Automatic medical diagnosis is an example of new applications using a different dat...

Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach.

PloS one
With the novel COVID-19 pandemic disrupting and threatening the lives of millions, researchers and clinicians have been recently conducting clinical trials at an unprecedented rate to learn more about the virus and potential drugs/treatments/vaccines...

Can natural language processing help differentiate inflammatory intestinal diseases in China? Models applying random forest and convolutional neural network approaches.

BMC medical informatics and decision making
BACKGROUND: Differentiating between ulcerative colitis (UC), Crohn's disease (CD) and intestinal tuberculosis (ITB) using endoscopy is challenging. We aimed to realize automatic differential diagnosis among these diseases through machine learning alg...

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

Molecular genetics & genomic medicine
BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an...

De-identifying free text of Japanese electronic health records.

Journal of biomedical semantics
BACKGROUND: Recently, more electronic data sources are becoming available in the healthcare domain. Electronic health records (EHRs), with their vast amounts of potentially available data, can greatly improve healthcare. Although EHR de-identificatio...

Extracting and classifying diagnosis dates from clinical notes: A case study.

Journal of biomedical informatics
Myeloproliferative neoplasms (MPNs) are chronic hematologic malignancies that may progress over long disease courses. The original date of diagnosis is an important piece of information for patient care and research, but is not consistently documente...