AIMC Topic: Natural Language Processing

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Inferring Clinical Correlations from EEG Reports with Deep Neural Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Successful diagnosis and management of neurological dysfunction relies on proper communication between the neurologist and the primary physician (or other specialists). Because this communication is documented within medical records, the ability to a...

Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extraction of ADR information can be crucial for healthcare providers, drug manufacturers, and consumers. ...

Detection of Suicidality in Adolescents with Autism Spectrum Disorders: Developing a Natural Language Processing Approach for Use in Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Over 15% of young people with autism spectrum disorders (ASD) will contemplate or attempt suicide during adolescence. Yet, there is limited evidence concerning risk factors for suicidality in childhood ASD. Electronic health records (EHRs) can be use...

Detecting Evidence of Intra-abdominal Surgical Site Infections from Radiology Reports Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Free-text reports in electronic health records (EHRs) contain medically significant information - signs, symptoms, findings, diagnoses - recorded by clinicians during patient encounters. These reports contain rich clinical information which can be le...

Intelligent Word Embeddings of Free-Text Radiology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Radiology reports are a rich resource for advancing deep learning applications in medicine by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to th...

Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies.

Journal of biomedical informatics
PURPOSE: This paper reports on a generic framework to provide clinicians with the ability to conduct complex analyses on elaborate research topics using cascaded queries to resolve internal time-event dependencies in the research questions, as an ext...

Mixed deep learning and natural language processing method for fake-food image recognition and standardization to help automated dietary assessment.

Public health nutrition
OBJECTIVE: The present study tested the combination of an established and a validated food-choice research method (the 'fake food buffet') with a new food-matching technology to automate the data collection and analysis.

Clinical Natural Language Processing in languages other than English: opportunities and challenges.

Journal of biomedical semantics
BACKGROUND: Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than Engli...

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four hea...