Data for AI in Congenital Heart Defects: Systematic Review.

Congenital heart disease (CHD) represents a significant challenge in prenatal care due to low prenatal detection rates. Artificial Intelligence (AI) offers promising avenues for precise CHD prediction. In this study we conducted a systematic review according to the PRISMA guidelines, investigating the landscape of AI applications in prenatal CHD detection.

HL7 FHIR in Health Research: A FHIR Specification for Metadata in Clinical, Epidemiological, and Public Health Studies.

This work presents the Fast Healthcare Interoperability Resources (FHIR®) specification of the NFDI4Health Metadata schema based on FHIR Version 4: We created 16 profiles to facilitate the integration of clinical, epidemiological, and public health study data. Despite challenges arising from the extensive MDS as well as missing concepts in semantic standards, it marks a significant advance in applying information technology standards to health research.

Towards an Interoperability Landscape for a National Research Data Infrastructure for Personal Health Data.

The German initiative "National Research Data Infrastructure for Personal Health Data" (NFDI4Health) focuses on research data management in health research. It aims to foster and develop harmonized informatics standards for public health, epidemiological studies, and clinical trials, facilitating access to relevant data and metadata standards. This publication lists syntactic and semantic data standards of potential use for NFDI4Health and beyond, based on interdisciplinary meetings and workshops, mappings of study questionnaires and the NFDI4Health metadata schema, and literature search.

Artificial Intelligence Bias in Health Care: Web-Based Survey.

Background: Resources are increasingly spent on artificial intelligence (AI) solutions for medical applications aiming to improve diagnosis, treatment, and prevention of diseases. While the need for transparency and reduction of bias in data and algorithm development has been addressed in past studies, little is known about the knowledge and perception of bias among AI developers.

Objective: This study's objective was to survey AI specialists in health care to investigate developers' perceptions of bias in AI algorithms for health care applications and their awareness and use of preventative measures.

Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review.

Background: The standard Fast Healthcare Interoperability Resources (FHIR) is widely used in health information technology. However, its use as a standard for health research is still less prevalent. To use existing data sources more efficiently for health research, data interoperability becomes increasingly important.

Implementing SNOMED CT in Open Software Solutions to Enhance the Findability of COVID-19 Questionnaires.

SNOMED CT fosters interoperability in healthcare and research. This use case implemented SNOMED CT for browsing COVID-19 questionnaires in the open-software solutions OPAL/MICA. We implemented a test server requiring files in a given YAML format for implementation of taxonomies with only two levels of hierarchy.

Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research.

Adopting international standards within health research communities can elevate data FAIRness and widen analysis possibilities. The purpose of this study was to evaluate the mapping feasibility against HL7® Fast Healthcare Interoperability Resources® (FHIR)® of a generic metadata schema (MDS) created for a central search hub gathering COVID-19 health research (studies, questionnaires, documents = MDS resource types). Mapping results were rated by calculating the percentage of FHIR coverage.

Fetal Echocardiography in Predicting Postnatal Outcome in Borderline Left Ventricle.

Objectives:  Prenatal prediction of postnatal univentricular versus biventricular circulation in patients with borderline left ventricle (bLV) remains challenging. This study investigated prenatal fetal echocardiographic parameters and postnatal outcome of patients with a prenatally diagnosed bLV.

Methods:  We report a retrospective study of bLV patients at four prenatal centers with a follow-up of one year.

Evaluating Suitability of SNOMED CT in Structured Searches for COVID-19 Studies.

Studies investigating the suitability of SNOMED CT in COVID-19 datasets are still scarce. The purpose of this study was to evaluate the suitability of SNOMED CT for structured searches of COVID-19 studies, using the German Corona Consensus Dataset (GECCO) as example. Suitability of the international standard SNOMED CT was measured with the scoring system ISO/TS 21564, and intercoder reliability of two independent mapping specialists was evaluated.

Prenatal Diagnosis and Postnatal Outcome of Eight Cases with Criss-Cross Heart - A Multicenter Case Series.

Objective:  Criss-cross heart (CCH) is a rare congenital cardiac defect defined by crossing of ventricular inflow streams contributing to less than 0.1 % of all congenital heart anomalies. Due to its rarity and complexity, prenatal diagnosis in these patients remains challenging.

Prenatal Diagnosis and Outcome of Congenital Corrected Transposition of the Great Arteries - A Multicenter Report of 69 Cases.

Objective:  Congenital corrected transposition of the great arteries (ccTGA) is a rare congenital cardiac anomaly which remains difficult to diagnose prenatally. We aim to investigate the natural history, associated anomalies and the outcome of patients in prenatally diagnosed ccTGA.

Method:  This was an international multicenter retrospective analysis of fetuses with a diagnosis of ccTGA from 2002 to 2017.