AIMC Topic: Electronic Health Records

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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...

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...

Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance.

The Journal of infectious diseases
There is growing excitement about the clinical use of artificial intelligence and machine learning (ML) technologies. Advancements in computing and the accessibility of ML frameworks enable researchers to easily train predictive models using electron...

Tailoring Risk Prediction Models to Local Populations.

JAMA cardiology
IMPORTANCE: Risk estimation is an integral part of cardiovascular care. Local recalibration of guideline-recommended models could address the limitations of existing tools.

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...

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...

TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision mana...

Adapting Large Language Models for Automated Summarisation of Electronic Medical Records in Clinical Coding.

Studies in health technology and informatics
Encapsulating a patient's clinical narrative into a condensed, informative summary is indispensable to clinical coding. The intricate nature of the clinical text makes the summarisation process challenging for clinical coders. Recent developments in ...