AIMC Topic: Natural Language Processing

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LLM-Based Medical Document Evaluation: Integrating Human Expert Insights.

Studies in health technology and informatics
Large Language Models (LLMs) show potential in medical document generation, but ensuring reliability requires extensive expert involvement, limiting clinical applications. To address this challenge, we developed an LLM-based evaluation framework with...

Automated Detection of Invasive Fungal Infections in Clinical Reports Using Medical Language Models.

Studies in health technology and informatics
Invasive fungal infections (IFIs) pose significant risks to patients with weakened immune systems, requiring timely detection. To improve IFI detection from clinical reports, we explore the value of recent advances in NLP techniques for this task, in...

Structured LLM Augmentation for Clinical Information Extraction.

Studies in health technology and informatics
Information extraction tasks, such as Named Entity Recognition (NER) and Relation Extraction (RE), are essential for advancing clinical research and applications. However, these tasks are hindered by the scarcity of labeled clinical documents due to ...

Readability Assessment and Comparison of Large Language Model-Generated Summaries of Trial Descriptions on ClinicalTrials.gov.

Studies in health technology and informatics
This study evaluated the readability of ClinicalTrials.gov trial information using traditional readability measures (TRMs) and compared it to summaries generated by large language models (LLMs), specifically ChatGPT and a fine-tuned BART-Large-CNN (F...

Improving Radiology Report Generation with Semantic Understanding.

Studies in health technology and informatics
This study proposes RRG-LLM, a model designed to enhance RRG by effectively learning medical domain with minimal computational resources. Initially, LLM is finetuned by LoRA, enabling efficient adaptation to the medical domain. Subsequently, only the...

Automated Pressure Injury Assessment and Documentation Generation Using Vision-Language Model.

Studies in health technology and informatics
Pressure injury assessment and documentation are crucial but time-consuming tasks in healthcare settings, with current inter-rater reliability among assessors only reaching 60-70%. This study presents an automated approach using the Florence-2 vision...

Fada: Fetal Accurate Detection AI for Automated Ultrasound Image Analysis and Reporting.

Studies in health technology and informatics
This study introduces Fetal Accurate Detection AI (FADA) an advanced AI-driven framework for generating clinically relevant descriptions from fetal ultrasound images, specifically focused on diverse anatomical structures and views, including trans-ab...

Efficient Maintenance of Large-Scale Medical Dictionaries Using Large Language Models: A Case for Biomarkers.

Studies in health technology and informatics
Dictionaries are essential in natural language processing and provide significant value across tasks; however, their construction and maintenance are expensive. Leveraging manual revision histories to suggest automatic corrections for unedited terms ...

Leveraging Retrieval Augmented Generation-Driven Large Language Models to Extract Dementia Agitation Symptoms and Triggers from Free-Text Nursing Notes.

Studies in health technology and informatics
Unstructured electronic health records are a rich source of patient-specific information but are challenging for analysis due to inconsistent terminology, diverse data formats, and extensive free-text content. To address this, we developed a named en...

Beyond GPT-NER: ChatGPT as Ensemble Arbitrator for Discontinuous Named Entity Recognition in Health Corpora.

Studies in health technology and informatics
In medicine and healthcare, NER (Named Entity Recognition) involves identifying clinically relevant entities such as medications, symptoms, and adverse drug events (ADEs). This task is particularly challenging due to discontinuous NER (DNER), fragmen...