AIMC Topic: Electronic Health Records

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Explainable Machine Learning Based Prediction of Severity of Heart Failure Using Primary Electronic Health Records.

Studies in health technology and informatics
Heart Failure (HF) is a life-threatening condition. It affects more than 64 million people worldwide. Early diagnosis of HF is extremely crucial. In this study, we propose utilization of machine learning (ML) models to predict severity of HF from pri...

Integrating Chatbot Functionality in a Patient Summary Based Healthcare System.

Studies in health technology and informatics
The integration of chatbots in healthcare has gained attention due to their potential to enhance patient engagement and satisfaction. This paper presents a healthcare chatbot providing comprehensive access to patient summaries, aligned with the Europ...

Comparing NER Approaches on French Clinical Text, with Easy-to-Reuse Pipelines.

Studies in health technology and informatics
The task of Named Entity Recognition (NER) is central for leveraging the content of clinical texts in observational studies. Indeed, texts contain a large part of the information available in Electronic Health Records (EHRs). However, clinical texts ...

Unsupervised Extraction of Body-Text from Clinical PDF Documents.

Studies in health technology and informatics
Automatic extraction of body-text within clinical PDF documents is necessary to enhance downstream NLP tasks but remains a challenge. This study presents an unsupervised algorithm designed to extract body-text leveraging large volume of data. Using D...

Semantic Mapping of Named-Entities in openEHR Templates and Ad-hoc Generation of Compositions.

Studies in health technology and informatics
Integration of free texts from reports written by physicians to an interoperable standard is important for improving patient-centric care and research in the medical domain. In the context of unstructured clinical data, NLP Information Extraction ser...

OntoBridge Versus Traditional ETL: Enhancing Data Standardization into CDM Formats Using Ontologies Within the DATOS-CAT Project.

Studies in health technology and informatics
Common Data Models (CDMs) enhance data exchange and integration across diverse sources, preserving semantics and context. Transforming local data into CDMs is typically cumbersome and resource-intensive, with limited reusability. This article compare...

Methods and Algorithms of Ensuring Data Privacy in AI-Based Healthcare Systems and Technologies.

Studies in health technology and informatics
This project seeks to devise novel algorithms and techniques leveraged in healthcare to guarantee data privacy in AI-powered systems. To bolster its credibility, the study review presents various modern approaches and technologies used to preserve da...

Developing a Generative AI-Powered Chatbot for Analyzing MAUDE Database.

Studies in health technology and informatics
This paper presents a chatbot that simplifies accessing and understanding the open-access records of adverse events related to medical devices in the MAUDE database. The chatbot is powered by generative AI technology, enabling count and search querie...

Leveraging Clinical Data Treasures: Integration of an AI Platform into Clinical IT.

Studies in health technology and informatics
In recent years, there has been a rapid growth in the use of AI in the clinical domain. In order to keep pace with this development, a framework should be created in which clinical AI models can be easily trained, managed and applied. In our study, w...

Automatic Extraction of Medication Data from Semi-Structured Prescriptions.

Studies in health technology and informatics
In many healthcare facilities, the prescription of drugs is done only in a semi-structured manner, using free-text fields where various information is often mixed. Therefore, automatic processing, especially for secondary use such as research purpose...