AIMC Topic: Vocabulary, Controlled

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Evaluating the state of the art in disorder recognition and normalization of the clinical narrative.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The ShARe/CLEF eHealth 2013 Evaluation Lab Task 1 was organized to evaluate the state of the art on the clinical text in (i) disorder mention identification/recognition based on Unified Medical Language System (UMLS) definition (Task 1a) a...

Multimodal medical information retrieval with unsupervised rank fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. H...

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based re...

Evaluating performance of biomedical image retrieval systems--an overview of the medical image retrieval task at ImageCLEF 2004-2013.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical image retrieval and classification have been extremely active research topics over the past 15 years. Within the ImageCLEF benchmark in medical image retrieval and classification, a standard test bed was created that allows researchers to com...

Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...

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...

Identifying Symptom Information in Clinical Notes Using Natural Language Processing.

Nursing research
BACKGROUND: Symptoms are a core concept of nursing interest. Large-scale secondary data reuse of notes in electronic health records (EHRs) has the potential to increase the quantity and quality of symptom research. However, the symptom language used ...

Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata.

Briefings in bioinformatics
Reusing massive collections of publicly available biomedical data can significantly impact knowledge discovery. However, these public samples and studies are typically described using unstructured plain text, hindering the findability and further reu...

Building a Natural Language Interface for FHIR Clinical Terminology Server.

Studies in health technology and informatics
While Fast Healthcare Interoperability Resources (FHIR) clinical terminology server enables quick and easy search and retrieval of coded medical data, it still has some drawbacks. When searching, any typographical errors, variations in word forms, or...