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Drug Labeling

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Augmented Reality: Real-Time Information Concerning Medication Consumed by a Patient.

Studies in health technology and informatics
This paper describes a mobile prototype capable of recognizing characters from a photograph of a medication package. The prototype was built to work on the iOS platform and was developed using Objective-C and C programming languages. The prototype, c...

Automatic Classification of Structured Product Labels for Pregnancy Risk Drug Categories, a Machine Learning Approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium
With regular expressions and manual review, 18,342 FDA-approved drug product labels were processed to determine if the five standard pregnancy drug risk categories were mentioned in the label. After excluding 81 drugs with multiple-risk categories, 8...

Searches for randomized controlled trials of drugs in MEDLINE and EMBASE using only generic drug names compared with searches applied in current practice in systematic reviews.

Research synthesis methods
BACKGROUND: It is unclear which terms should be included in bibliographic searches for randomized controlled trials (RCTs) of drugs, and identifying relevant drug terms can be extremely laborious. The aim of our analysis was to determine whether a bi...

Overlap in drug-disease associations between clinical practice guidelines and drug structured product label indications.

Journal of biomedical semantics
BACKGROUND: Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug structured product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medi...

DrugSemantics: A corpus for Named Entity Recognition in Spanish Summaries of Product Characteristics.

Journal of biomedical informatics
For the healthcare sector, it is critical to exploit the vast amount of textual health-related information. Nevertheless, healthcare providers have difficulties to benefit from such quantity of data during pharmacotherapeutic care. The problem is tha...

Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology.

Journal of biomedical informatics
INTRODUCTION: The FDA Adverse Event Reporting System (FAERS) is a primary data source for identifying unlabeled adverse events (AEs) in a drug or biologic drug product's postmarketing phase. Many AE reports must be reviewed by drug safety experts to ...

Advancing the State of the Art in Clinical Natural Language Processing through Shared Tasks.

Yearbook of medical informatics
OBJECTIVES:  To review the latest scientific challenges organized in clinical Natural Language Processing (NLP) by highlighting the tasks, the most effective methodologies used, the data, and the sharing strategies.

Natural language processing-based assessment of consistency in summaries of product characteristics of generic antimicrobials.

Pharmacology research & perspectives
To investigate consistency in summaries of product characteristics (SmPCs) of generic antimicrobials, we used natural language processing (NLP) to analyze and compare large amounts of text quantifying consistency between original and generic SmPCs. W...

Machine learning-based identification and rule-based normalization of adverse drug reactions in drug labels.

BMC bioinformatics
BACKGROUND: Use of medication can cause adverse drug reactions (ADRs), unwanted or unexpected events, which are a major safety concern. Drug labels, or prescribing information or package inserts, describe ADRs. Therefore, systematically identifying A...