AIMC Topic: Germany

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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...

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...

Applying AI to Support Categorization of Heterogeneous Epidemiological Datasets.

Studies in health technology and informatics
The significance of Findable, Accessible, Interoperable, and Reusable (FAIR) data is increasing, particularly in the context of enhancing data reuse in research. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) aims to...

Smoking Status Normalization with Cross-Encoders and SNOMED CT.

Studies in health technology and informatics
Accurately documenting smoking status is essential for clinical decision-making and patient care. However, smoking status information is often only available in clinical narratives. Mapping smoking-related terms to standardized terminologies such as ...

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...

Using Machine Learning for the Fusion of Tumor Records on a Real-World Dataset.

Studies in health technology and informatics
Cancer registries collect multiple reports describing the same tumor, potentially leading to duplicate or conflicting values across different records. This complicates further use of cancer data. Data fusion addresses this issue by consolidating mult...

Federated Learning for Predictive Analytics in Weaning from Mechanical Ventilation.

Studies in health technology and informatics
Mechanical ventilation is crucial for critically ill patients in ICUs, requiring accurate weaning and extubations timing for optimal outcomes. Current prediction models struggle with generalizability across datasets like MIMIC-IV and eICU-CRD. We pro...

Hierarchical clustering analysis & machine learning models for diagnosing skeletal classes I and II in German patients.

BMC oral health
BACKGROUND: Classification is one of the most common tasks in artificial intelligence (AI) driven fields in dentistry and orthodontics. The AI abilities can significantly improve the orthodontist's critical mission to diagnose and treat patients prec...

Patients' Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) is increasingly used in medical care, particularly in the areas of image recognition and processing. While its practical use in other areas is still limited, an understanding of patients' needs is essential fo...

Cost-effectiveness of opportunistic osteoporosis screening using chest radiographs with deep learning in Germany.

Aging clinical and experimental research
BACKGROUND: Osteoporosis is often underdiagnosed due to limitations in traditional screening methods, leading to missed early intervention opportunities. AI-driven screening using chest radiographs could improve early detection, reduce fracture risk,...