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Natural Language Processing - AI Medical Compendium

AIMC Topic: Natural Language Processing

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German Medical NER with BERT and LLMs: The Impact of Training Data Size.

Studies in health technology and informatics
Named Entity Recognition (NER) in the medical domain often presents significant challenges due to the complexity and specificity of medical terminology, especially in lower-resource settings where annotated data is scarce. This study explores the per...

Fake It till You Predict It: Data Augmentation Strategies to Detect Initiation and Termination of Oncology Treatment.

Studies in health technology and informatics
At the hospital, the dispersion of information regarding anti-cancer treatment makes it difficult to extract. We proposed a solution capable of identifying dates, drugs and their temporal relationship within free-text oncology reports with very few m...

Exploring Zero-Shot Cross-Lingual Biomedical Concept Normalization via Large Language Models.

Studies in health technology and informatics
Over the past few years, discriminative and generative large language models (LLMs) have emerged as the predominant approaches in natural language processing. However, despite significant advancements, there remains a gap in comparing the performance...

Chain of Thought Strategy for Smaller LLMs for Medical Reasoning.

Studies in health technology and informatics
This paper investigates the application of Chain of Thought (CoT) reasoning to enhance the performance of smaller language models in medical question-answering tasks. By leveraging CoT prompting strategies, we aim to improve model accuracy and interp...

Leveraging Large Language Models for Synthetic Data Generation to Enhance Adverse Drug Event Detection in Tweets.

Studies in health technology and informatics
Adverse drug event (ADE) detection in social media texts poses significant challenges due to the informal nature of the text and the limited availability of annotations. The scarcity of ADE named entity recognition (NER) datasets for social media hin...

Transforming Data from a Commercial Hospital Information System into FHIR.

Studies in health technology and informatics
The expanded use of hospital information systems in recent decades offers possibilities to use data collected in the clinical routine not only for individual patient care, but also for medical research. For this purpose, it is important use standardi...

Conversion of Nursing Statements into the OMOP Common Data Model.

Studies in health technology and informatics
The aim of this study is to convert nursing statements into the OMOP CDM for use in observational studies. We mapped nursing statements to SNOMED CT concepts and converted them into the OMOP CDM format through an ETL process. As a result, approximate...

FLANDERS: Fast Learning COVID-19 Care System.

Studies in health technology and informatics
The COVID-19 pandemic highlighted the complexities of diagnosing and managing acute Respiratory Failure (RF). Early prediction of RF remains a key challenge, with no established tools currently available. This study developed a machine learning model...

Utilising Machine Learning for Better Mental Health and Decision Making: A Case Study of Timebanking UK.

Studies in health technology and informatics
This study explores how the integration of predictive models with machine learning and natural language processing can optimise community-based service operations, using Timebanking UK as a case study. The research evaluated these models in terms of ...

Participatory Co-Creation of an AI-Supported Patient Information System: A Multi-Method Qualitative Study.

Studies in health technology and informatics
In radiology and other medical fields, informed consent often rely on paper-based forms, which can overwhelm patients with complex terminology. These forms are also resource-intensive. The KIPA project addresses these challenges by developing an AI-a...