AIMC Topic: Natural Language Processing

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Automatic Annotation of Disposition Counts in News Articles.

Studies in health technology and informatics
News media aggregate and report disposition counts during crises: how many people are affected, suspected affected, have died, and have recovered or been recovered; and they tend to do so in a timely and trustworthy manner. We present and evaluate a ...

Large Language Model-Assisted Systematic Review: Validation Based on Cochrane Review Data.

Studies in health technology and informatics
Large Language Models (LLMs) offer potential for automating systematic reviews, a labor-intensive process in evidence-based medicine. We evaluated GPT-4o, GPT-4o-mini, and Llama 3.1:8B on abstract screening and risk of bias assessment using 12 Cochra...

Automating Data Extraction from PDF Sleep Reports Using Data Mining Techniques.

Studies in health technology and informatics
This work introduces a web application for extracting, processing, and visualizing data from sleep studies reports. Using Optical Character Recognition (OCR) and Natural Language Processing (NLP), the pipeline extracts over 75 key data points from fo...

Domain Shift in Part-of-Speech Tagging.

Studies in health technology and informatics
This study highlights domain shift in dataset distributions that impact machine learning performance in clinical natural language processing, analyzing linguistic differences across clinical narratives, biomedical abstracts, and news articles in Engl...

Building the Infrastructure for the German Medical Text Corpus Project (GeMTeX).

Studies in health technology and informatics
The German Medical Text Project (GeMTeX) is one of the largest infrastructure efforts for German-language clinical documents. To determine the different starting points of the participating institutions, we conducted a survey regarding standards, ann...

Detecting Adverse Drug Events in Clinical Notes Using Large Language Models.

Studies in health technology and informatics
Monitoring adverse drug events (ADEs) is critical for pharmacovigilance and patient safety. However, identifying ADEs remains challenging, as suspected or confirmed side effects are often documented solely in the unstructured text of electronic healt...

Delirium Identification from Nursing Reports Using Large Language Models.

Studies in health technology and informatics
This study investigates large language models for delirium detection from nursing reports, comparing keyword matching, prompting, and finetuning. Using a manually labelled dataset from the University Hospital Freiburg, Germany, we tested Llama3 and P...

Exploring the Potential of GPT-4 in Creating Billing Codes from Clinic Notes.

Studies in health technology and informatics
Creating standardized billing codes from clinic notes is challenging due to the complexity of over 22,000 codes and the unstructured nature of medical records. This paper investigates how well GPT-4, can automate CPT/HCPCS codes generation. To assess...

Transformer-Based Multilabel NER Using Wikipedia Corpora in Multiple Languages.

Studies in health technology and informatics
The high cost of manual data labeling and privacy concerns result in a considerable dearth of medical annotations in non-English texts. Recent work by Frank and Kramer [1] introduces an unsupervised approach for constructing an ontology-annotated cor...

Evaluating LLMs' Potential to Identify Rare Patient Identifiers in Patient Health Records.

Studies in health technology and informatics
This study explores the utility of Large Language Models (LLMs) to support finding rare patient record details that could make a patient identifiable. Whilst most research has focused on what we call direct patient identifiers, indirect patient ident...