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The ISO/IEEE 11073-10207 Domain Information and Service Model focuses on cross-manufacturer device-to-device communication, whereas HL7 Fast Healthcare Interoperability Resources (FHIR) support the data exchange between software systems in health care. The contents of both standards overlap, yet they differ in structure. In this work, we present an Implementation Guide that contains a mapping of medical device data from ISO/IEEE 11073-10207 to HL7 FHIR in order to improve vendor-independent interoperability. This Implementation Guide helps to bridge the structural interoperability gap between these two communication architectures for medical devices and clinical information systems. This furthermore promotes the reuse of medical device data, e.g. for clinical research purposes.To facilitate the mapping while retaining contextual information despite the structural differences, it was only necessary to create five profiles for two FHIR resources. This Implementation Guide is described in relation to similar efforts including difficulties that arose during the implementation of the mapping. Approximately 25 problems occurred, but in all cases they are not critical and most of them could be solved for our use cases. In the future, this work will be merged with the Implementation Guide for point-of-care medical devices.

Background/Objectives: The integration of machine learning into the domain of radiomics has revolutionized the approach to personalized medicine, particularly in oncology. Our research presents RadTA (RADiomics Trend Analysis), a novel framework developed to facilitate the automatic analysis of quantitative imaging biomarkers (QIBs) from time-series CT volumes. Methods: RadTA is designed to bridge a technical gap for medical experts and enable sophisticated radiomic analyses without deep learning expertise. The core of RadTA includes an automated command line interface, streamlined image segmentation, comprehensive feature extraction, and robust evaluation mechanisms. RadTA utilizes advanced segmentation models, specifically TotalSegmentator and Body Composition Analysis (BCA), to accurately delineate anatomical structures from CT scans. These models enable the extraction of a wide variety of radiomic features, which are subsequently processed and compared to assess health dynamics across timely corresponding CT series. Results: The effectiveness of RadTA was tested using the HNSCC-3DCT-RT dataset, which includes CT scans from oncological patients undergoing radiation therapy. The results demonstrate significant changes in tissue composition and provide insights into the physical effects of the treatment. Conclusions: RadTA demonstrates a step of clinical adoption in the field of radiomics, offering a user-friendly, robust, and effective tool for the analysis of patient health dynamics. It can potentially also be used for other medical specialties. [ABSTRACT FROM AUTHOR]

The efficient direct integration of real-time medical device data is a promising approach to improve patient care enabling a direct and eminent intervention. This study presents a comprehensive approach for integrating real-time medical device data into clinical environments using the HL7® FHIR® standards and IEEE 11073 Service-Oriented Device Connectivity (SDC). The study proposes a conceptual framework and an opensource proof-of-concept implementation for real-time data integration within the Medical Data Integration Center (MeDIC) at UKSH. Key components include a selective recording mechanism to mitigate storage issues and ensure accurate data capture. Our robust network architecture utilizes Kafka brokers for seamless data transfer in isolated networks. The study demonstrates the selective capturing of real-time data within a clinical setting to enable medical device data for a down-stream processing and analysis. [ABSTRACT FROM AUTHOR]

Imaging techniques are a cornerstone of today's medicine and can be crucial for a successful therapy. But in addition, the generated imaging series are an important resource for new informatics' methods, especially in the field of artificial intelligence. This paper describes the success of integrating clinical routine imaging data into a standardized format for research purposes. Thus, we designed an integration flow and successfully implemented it in the local data integration center of University Hospital Schleswig-Holstein. The flow integrates imaging series and radiological reports from the primary system into an openEHR repository with enrichment by semantic codes for better findability and retrieval using HL7 FHIR. As a result, 6.6 million radiological studies with 29 million image series are now available for further medical (informatics) research. [ABSTRACT FROM AUTHOR]

Copyright of Sexuologie is the property of Deutsche Gesellschaft fur Sexualmedizin, Sexualtherapie & Sexualwissenschaft e.V. (DGSMTW) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sexuologie is the property of Deutsche Gesellschaft fur Sexualmedizin, Sexualtherapie & Sexualwissenschaft e.V. (DGSMTW) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sexuologie is the property of Deutsche Gesellschaft fur Sexualmedizin, Sexualtherapie & Sexualwissenschaft e.V. (DGSMTW) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The utilisation of metadata repositories increasingly promotes secondary use of routinely collected data. However, this has not yet solved the problem of data exchange across organisational boundaries. The local description of a metadata set must also be exchangeable for flawless data exchange. In previous work, a metadata exchange language QL 4 MDR was developed. This work aimed to examine the applicability of this exchange language. For this purpose, existing MDR implementations were identified and systematically inspected and roughly divided into two categories to distinguish between data integration and query integration. It has been shown that all the implementations can be adapted to QL 4 MDR. The integration of metadata is an important first step; it enables the exchange of information, which is so urgently needed for the further processing of instance data, from the metadata mappings to the transformation rules. [ABSTRACT FROM AUTHOR]

Whenever medical data is integrated from multiple sources, it is regarded good practice to separate data from information about its meaning, such as designations, definitions or permissible values (in short: metadata). However, the ways in which applications work with metadata are imperfect: Many applications do not support fetching metadata from externalized sources such as metadata repositories. In order to display human-readable metadata in any application, we propose not to change the application, but to provide a library that makes a change to the user interface. The goal of this work is to provide a way to "inject" the meaning of metadata keys into the web-based frontend of an application to make it "metadata aware" [ABSTRACT FROM AUTHOR]