AIMC Topic: Natural Language Processing

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Assessing the Utility of Automatic Cancer Registry Notifications Data Extraction from Free-Text Pathology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer Registries record cancer data by reading and interpreting pathology cancer specimen reports. For some Registries this can be a manual process, which is labour and time intensive and subject to errors. A system for automatic extraction of cance...

Knowledge Extraction from MEDLINE by Combining Clustering with Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The identification of relevant predicates between co-occurring concepts in scientific literature databases like MEDLINE is crucial for using these sources for knowledge extraction, in order to obtain meaningful biomedical predications as subject-pred...

Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We propose Latent Class Allocation (LCA) and Discriminative Labeled Latent Dirichlet Allocation (DL-LDA), two novel interpretable probabilistic latent variable models for automatic annotation of clinical text. Both models separate the terms that are ...

Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...

A Study of Concept Extraction Across Different Types of Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Our research investigates methods for creating effective concept extractors for specialty clinical notes. First, we present three new "specialty area" datasets consisting of Cardiology, Neurology, and Orthopedics clinical notes manually annotated wit...

An Ensemble Method for Spelling Correction in Consumer Health Questions.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Orthographic and grammatical errors are a common feature of informal texts written by lay people. Health-related questions asked by consumers are a case in point. Automatic interpretation of consumer health questions is hampered by such errors. In th...

Reviewing 741 patients records in two hours with FASTVISU.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The secondary use of electronic health records opens up new perspectives. They provide researchers with structured data and unstructured data, including free text reports. Many applications been developed to leverage knowledge from free-text reports,...

POETenceph - Automatic identification of clinical notes indicating encephalopathy using a realist ontology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Identifying inpatients with encephalopathy is important. The disorder is prevalent, often missed, and puts patients at risk. We describe POETenceph, natural language processing pipeline, which ranks clinical notes on the extent to which they indicate...

Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Digestive diseases and sciences
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computa...