AIMC Topic: Natural Language Processing

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Zero-Shot LLMs for Named Entity Recognition: Targeting Cardiac Function Indicators in German Clinical Texts.

Studies in health technology and informatics
INTRODUCTION: Large Language Models (LLMs) like ChatGPT have become increasingly prevalent. In medicine, many potential areas arise where LLMs may offer added value. Our research focuses on the use of open-source LLM alternatives like Llama 3, Gemma,...

Classification of Veterinary Subjects in Medical Literature and Clinical Summaries.

Studies in health technology and informatics
INTRODUCTION: Human and veterinary medicine are practiced separately, but literature databases such as Pubmed include articles from both fields. This impedes supporting clinical decisions with automated information retrieval, because treatment consid...

Extending the TOP Framework with an Ontology-Based Text Search Component.

Studies in health technology and informatics
INTRODUCTION: Constructing search queries that deal with complex concepts is a challenging task without proficiency in the underlying query language - which holds true for either structured or unstructured data. Medical data might encompass both type...

Recognition and normalization of multilingual symptom entities using in-domain-adapted BERT models and classification layers.

Database : the journal of biological databases and curation
Due to the scarcity of available annotations in the biomedical domain, clinical natural language processing poses a substantial challenge, especially when applied to low-resource languages. This paper presents our contributions for the detection and ...

Integrating deep learning architectures for enhanced biomedical relation extraction: a pipeline approach.

Database : the journal of biological databases and curation
Biomedical relation extraction from scientific publications is a key task in biomedical natural language processing (NLP) and can facilitate the creation of large knowledge bases, enable more efficient knowledge discovery, and accelerate evidence syn...

Large Language Models in Nursing Education: State-of-the-Art.

Studies in health technology and informatics
This study explores the integration of Large Language Models (LLMs) into nursing education, highlighting a paradigm shift towards interactive learning environments. We aimed to analyze the literature to identify how large language models are being im...

What Kind of Transformer Models to Use for the ICD-10 Codes Classification Task.

Studies in health technology and informatics
Coding according to the International Classification of Diseases (ICD)-10 and its clinical modifications (CM) is inherently complex and expensive. Natural Language Processing (NLP) assists by simplifying the analysis of unstructured data from electro...

Using Retrieval-Augmented Generation to Capture Molecularly-Driven Treatment Relationships for Precision Oncology.

Studies in health technology and informatics
Modern generative artificial intelligence techniques like retrieval-augmented generation (RAG) may be applied in support of precision oncology treatment discussions. Experts routinely review published literature for evidence and recommendations of tr...

Optimizing Data Extraction: Harnessing RAG and LLMs for German Medical Documents.

Studies in health technology and informatics
In the field of medical data analysis, converting unstructured text documents into a structured format suitable for further use is a significant challenge. This study introduces an automated local deployed data privacy secure pipeline that uses open-...

Unveiling Medical Insights: Advanced Topic Extraction from Scientific Articles.

Studies in health technology and informatics
In the ever-evolving landscape of medical research and healthcare, the abundance of scientific articles presents both a treasure trove of knowledge and a daunting challenge. Researchers, clinicians, and data scientists grapple with vast amounts of un...