Programming techniques for improving rule readability for rule-based information extraction natural language processing pipelines of unstructured and semi-structured medical texts.

Background: Extraction of medical terms and their corresponding values from semi-structured and unstructured texts of medical reports can be a time-consuming and error-prone process. Methods of natural language processing (NLP) can help define an extraction pipeline for accomplishing a structured format transformation strategy.

Objectives: In this paper, we build an NLP pipeline to extract values of the classification of malignant tumors (TNM) from unstructured and semi-structured pathology reports and import them further to a structured data source for a clinical study.

Structured, Harmonized, and Interoperable Integration of Clinical Routine Data to Compute Heart Failure Risk Scores.

Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format.

openEHR-to-FHIR: Converting openEHR Compositions to Fast Healthcare Interoperability Resources (FHIR) for the German Corona Consensus Dataset (GECCO).

The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named "openEHR-to-FHIR" that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles.

Transformation of microbiology data into a standardised data representation using OpenEHR.

The spread of multidrug resistant organisms (MDRO) is a global healthcare challenge. Nosocomial outbreaks caused by MDRO are an important contributor to this threat. Computer-based applications facilitating outbreak detection can be essential to address this issue.

A Report on Archetype Modelling in a Nationwide Data Infrastructure Project.

Background: The nationwide data infrastructure project HiGHmed strives for achieving semantic interoperability through the use of openEHR archetypes. Therefore, a knowledge governance framework defining collaborative modelling processes has been established. For long-sustained success and the creation of high-quality archetypes, continuous monitoring is vital.

Simultaneous monitoring of different vitrification solution components permeating into tissues.

Cryopreservation can be used for long-term preservation of tissues and organs. It relies on using complex mixtures of cryoprotective agents (CPAs) to reduce the damaging effects of freezing, but care should be taken to avoid toxic effects of CPAs themselves. In order to rationally design cryopreservation strategies for tissues, it is important to precisely determine permeation kinetics of the protectants that are used to ensure maximum permeation, while minimizing the exposure time and toxicity effects.