AIMC Topic: Natural Language Processing

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Enhancing Arden-Syntax-Based Clinical Reasoning with Ontologies.

Studies in health technology and informatics
We present a new methodological approach based on integrating Arden-Syntax-based clinical decision support (CDS) with an upstream ontology service. Incoming linguistic patient data, such as single reports about detected germs or viruses, shall be ide...

AI-Assisted Application for Pediatric Drug Dosing.

Studies in health technology and informatics
Technology in the medical field is continuously advancing due to its numerous subdomains and the ever-growing medical needs of people. Information systems have become integral to doctors' daily routines in patient care, offering flexibility and suppo...

FHIR-Based Arden Syntax Compiler for Clinical Decision Support.

Studies in health technology and informatics
The Arden Syntax is a language designed for the encoding of medical knowledge into clinical decision support systems. Its evolution is overseen by Health Level 7. A significant enhancement in its new version 3.0 is the incorporation of FHIR for data ...

Utilizing RAG and GPT-4 for Extraction of Substance Use Information from Clinical Notes.

Studies in health technology and informatics
This research investigates the application of a hybrid Retrieval-Augmented Generation (RAG) and Generative Pre-trained Transformer (GPT) pipeline for extracting and categorizing substance use information from unstructured clinical notes. The aim is t...

[Digitization in the diagnosis and treatment of headache].

MMW Fortschritte der Medizin
In recent years, machine learning, particularly Natural Language Processing, has emerged as a valuable tool for analyzing unstructured health data, such as headache anamneses. Studies demonstrate that algorithms can identify specific patterns and aut...

CACER: Clinical concept Annotations for Cancer Events and Relations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationship between cancer drugs and their associated symptom burden...

Relation extraction using large language models: a case study on acupuncture point locations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPTs) and Llama prese...

Generating colloquial radiology reports with large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Patients are increasingly being given direct access to their medical records. However, radiology reports are written for clinicians and typically contain medical jargon, which can be confusing. One solution is for radiologists to provide ...

Utilizing active learning strategies in machine-assisted annotation for clinical named entity recognition: a comprehensive analysis considering annotation costs and target effectiveness.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Active learning (AL) has rarely integrated diversity-based and uncertainty-based strategies into a dynamic sampling framework for clinical named entity recognition (NER). Machine-assisted annotation is becoming popular for creating gold-s...