AIMC Topic: Medical Errors

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A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic ...

Analysis of Critical Incident Reports Using Natural Language Processing.

Studies in health technology and informatics
UNLABELLED: A Critical Incident Reporting System (CIRS) collects anecdotal reports from employees, which serve as a vital source of information about incidents that could potentially harm patients.

A Machine Learning Approach to Reclassifying Miscellaneous Patient Safety Event Reports.

Journal of patient safety
BACKGROUND AND OBJECTIVES: Medical errors are a leading cause of death in the United States. Despite widespread adoption of patient safety reporting systems to address medical errors, making sense of the reports collected in these systems is challeng...

Artificial intelligence in liver disease.

Journal of gastroenterology and hepatology
Artificial intelligence (AI) is a branch of computer science that attempts to mimic human intelligence, such as learning and problem-solving skills. The use of AI in hepatology occurred later than in gastroenterology. Nevertheless, studies on applyin...

Can Unified Medical Language System-based semantic representation improve automated identification of patient safety incident reports by type and severity?

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to evaluate the feasibility of using Unified Medical Language System (UMLS) semantic features for automated identification of reports about patient safety incidents by type and severity.

Detecting Severe Incidents from Electronic Medical Records Using Machine Learning Methods.

Studies in health technology and informatics
The goal of this research was to design a solution to detect non-reported incidents, especially severe incidents. To achieve this goal, we proposed a method to process electronic medical records and automatically extract clinical notes describing sev...

Using convolutional neural networks to identify patient safety incident reports by type and severity.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To evaluate the feasibility of a convolutional neural network (CNN) with word embedding to identify the type and severity of patient safety incident reports.

Assessment of Critical Feeding Tube Malpositions on Radiographs Using Deep Learning.

Journal of digital imaging
Assess the efficacy of deep convolutional neural networks (DCNNs) in detection of critical enteric feeding tube malpositions on radiographs. 5475 de-identified HIPAA compliant frontal view chest and abdominal radiographs were obtained, consisting of ...

Named Entity Recognition and Classification for Medical Prospectuses.

Studies in health technology and informatics
Structuring and processing natural language is a growing challenge in the medical field. Researchers are looking for new ways to extract knowledge to create databases and applications to help doctors treat patients and minimize medical errors. A very...