MIKI Medical Informatics and Artificial Intelligence
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MIKI Medical Informatics and Artificial Intelligence
@mi-kiel.bsky.social
Medical Informatics and Artificial Intelligence @ Kiel University and University Hospital Schleswig-Holstein https://mi-ki.eu
Reposted by MIKI Medical Informatics and Artificial Intelligence
New JMIR MedInform: A Data-Centric Approach for #health Care and #research in a #health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study
A Data-Centric Approach for #health Care and #research in a #health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study
Background: In the evolving landscape of #health care, data use plays an ever-increasing role in #health care IT. However, data are often siloed and uncoded free text distributed across several IT systems. This paper introduces a #health knowledge management platform, designed to integrate, harmonize, and enable reuse of #health care and #medical #research data. The platform aims to bridge the gap between #research and #patient care, showcased through real-world scenarios, emphasizing data harmonization and knowledge management within a #health care institution. The study is based at the University Hospital Schleswig-Holstein. Objective: The main objective of this project is to design, implement, and evaluate a knowledge management platform that integrates #health care and bio#medical #research to support use cases in both domains. Methods: The study describes the “#health knowledge management platform” designed to access and gain knowledge from #health care and #medical #research data. We performed several rounds of focus groups with stakeholders to elicit the platform requirements. In the process, we identified key aspects of the platform. From the functional requirements, we designed an architectural concept. The platform evaluation follows the Framework for Evaluation in Design Science #research and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 25010 standard with a focus on key aspects identified and real-world scenarios. Two application scenarios, cardiology and radiology, are selected for a requirement-based, qualitative evaluation. Results: We show that our #health knowledge management platform is capable of integrating diverse data formats like #health Level 7 Version 2 messages, CSV exports, and #digital Imaging and Communications in Medicine. It currently integrates over 46 million admit, discharge, transfer messages, 38 million imaging studies, and structured clinical data for approximately 1.5 million #patients. The platform supports different scenarios based on its 5-layer architecture, including a clinical data repository and services like Master #patient Index and Consent Management. The evaluation against 39 predefined functional requirements showed our platform’s capability in certain real-world scenarios of cardiology and radiology. Our evaluation demonstrates that the platform covers the majority of the identified requirements to support knowledge management in #health care institutions. Conclusions: Our requirement-based evaluation of the #health knowledge management platform at University Hospital Schleswig-Holstein reveals its capabilities, which is possibly leading to better knowledge transfer between #patient care and #research. The platform’s architecture and standardized data improve the quality of data and facilitate access to knowledge. Ongoing development and potential quantitative measures will further enhance its applicability in dynamic #health care landscapes.
dlvr.it
April 30, 2026 at 5:24 PM
Publication alert!
Our team published our health knowledge management platform approach in JMIR MI. Read about the architecture of UKSH Medical Data Integration Center.

@jmirpub.bsky.social @bschreiweis.bsky.social @hannesulrich.bsky.social @uni-kiel.de #openEHR #FHIR #Interoperability
New JMIR MedInform: A Data-Centric Approach for #health Care and #research in a #health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study
A Data-Centric Approach for #health Care and #research in a #health Knowledge Management Platform: Implementation and Requirement-Based Evaluation Study
Background: In the evolving landscape of #health care, data use plays an ever-increasing role in #health care IT. However, data are often siloed and uncoded free text distributed across several IT systems. This paper introduces a #health knowledge management platform, designed to integrate, harmonize, and enable reuse of #health care and #medical #research data. The platform aims to bridge the gap between #research and #patient care, showcased through real-world scenarios, emphasizing data harmonization and knowledge management within a #health care institution. The study is based at the University Hospital Schleswig-Holstein. Objective: The main objective of this project is to design, implement, and evaluate a knowledge management platform that integrates #health care and bio#medical #research to support use cases in both domains. Methods: The study describes the “#health knowledge management platform” designed to access and gain knowledge from #health care and #medical #research data. We performed several rounds of focus groups with stakeholders to elicit the platform requirements. In the process, we identified key aspects of the platform. From the functional requirements, we designed an architectural concept. The platform evaluation follows the Framework for Evaluation in Design Science #research and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 25010 standard with a focus on key aspects identified and real-world scenarios. Two application scenarios, cardiology and radiology, are selected for a requirement-based, qualitative evaluation. Results: We show that our #health knowledge management platform is capable of integrating diverse data formats like #health Level 7 Version 2 messages, CSV exports, and #digital Imaging and Communications in Medicine. It currently integrates over 46 million admit, discharge, transfer messages, 38 million imaging studies, and structured clinical data for approximately 1.5 million #patients. The platform supports different scenarios based on its 5-layer architecture, including a clinical data repository and services like Master #patient Index and Consent Management. The evaluation against 39 predefined functional requirements showed our platform’s capability in certain real-world scenarios of cardiology and radiology. Our evaluation demonstrates that the platform covers the majority of the identified requirements to support knowledge management in #health care institutions. Conclusions: Our requirement-based evaluation of the #health knowledge management platform at University Hospital Schleswig-Holstein reveals its capabilities, which is possibly leading to better knowledge transfer between #patient care and #research. The platform’s architecture and standardized data improve the quality of data and facilitate access to knowledge. Ongoing development and potential quantitative measures will further enhance its applicability in dynamic #health care landscapes.
dlvr.it
May 4, 2026 at 3:28 PM
Publication alert!
New paper about our service annotating CT images with SNOMED CT and RadLex just got published in BMC Medical Informatics and Decision Making: doi.org/10.1186/s129... @hannesulrich.bsky.social @bschreiweis.bsky.social #IMPETUS #FHIR #SNOMEDCT #RadLex
Full-scale indexing and semantic annotation of CT imaging: boosting FAIRness - BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making - The integration of artificial intelligence into medicine has led to significant advances, particularly in diagnostics and treatment planning. However,...
doi.org
March 15, 2026 at 5:59 AM
Reposted by MIKI Medical Informatics and Artificial Intelligence
Publikation zur Kommunikation rund um die #ePA: Bott et al. „Wie wird die Datenspende zum Erfolgsmodell? Workshopbericht zu effektiven Kommunikations- und Vermittlungsstrategien für Bürger:innen und Patient:innen,“ GMS Med Inform Biom Epidemiol, vol. 22, iss. Doc01, 2026.
@gmds-ev.bsky.social
January 21, 2026 at 5:18 PM
Reposted by MIKI Medical Informatics and Artificial Intelligence
✨ Einladung zum MIRACUM-DIFUTURE Kolloquium ✨

📚 Thema: Struktur und Serviceportfolio des UKSH MeDIC
🗣 Referent: Prof. Dr. Björn Schreiweis (@bschreiweis.bsky.social) (@uni-kiel.de & UKSH)
📅 Wann: Dienstag, 28. Oktober 2025, um 16:45 Uhr
📍 Wo: Online via Zoom: bit.ly/4e9p3Ka
October 24, 2025 at 8:57 AM
#JustPublished Our latest publication “Integrating an AI platform into clinical IT: BPMN processes for clinical AI model development” just got published in #BMC Medical Informatics and Decision Making @springernature.com doi.org/10.1186/s129... #AI #Platform #Integration #healthcare
Integrating an AI platform into clinical IT: BPMN processes for clinical AI model development - BMC Medical Informatics and Decision Making
Background There has been a resurgence of Artificial Intelligence (AI) on a global scale in recent times, resulting in the development of cutting-edge AI solutions within hospitals. However, this has ...
doi.org
July 2, 2025 at 2:15 PM
L Mejia presenting her poster “Mind the Gap: Design Thinking and Human Centered Design for eHealth Applications - Insights from Vulnerable Populations in a Scoping Review” at #MIE2025 @efmieurope.bsky.social @gmds-ev.bsky.social @uni-kiel.de
May 19, 2025 at 3:18 PM
Benjamin Kinast from our team will be presenting our work on ‘Extracting LOINC Codes from a Laboratory Information System's Index: Addressing Semantic Interoperability with Web Scraping’ doi.org/10.3233/shti... at #dHealth25 in Vienna May 6th ‘Scientific Session #3’ 15:15-16:45 #ForschungLohntSich
IOS Press Ebooks - Extracting LOINC Codes from a Laboratory Information System’s Index: Addressing Semantic Interoperability with Web Scraping
doi.org
April 29, 2025 at 9:46 AM
Reposted by MIKI Medical Informatics and Artificial Intelligence
Das UKSH Datensymposium befasst sich mit dem Nutzungsmöglichkeiten und -wegen von Versorgungsdaten am UKSH, der @uniluebeck.bsky.social und der medizinischen Fakultät der @uni-kiel.de
#Medizininformatik #DIZ #Datennutzung #MedizinischeForschung #KlinischeTranslation
February 19, 2025 at 11:53 AM
Reposted by MIKI Medical Informatics and Artificial Intelligence
Calling for your paper for the upcoming collection
Challenges in health data management
I’m honored to be serving as the collection’s Guest Editor and eager to read your submission. Learn more about the collection and how to contribute:
bit.ly/3VRciO6
#digitalhealth #datamanagement #medinf
January 15, 2025 at 11:31 AM
Reposted by MIKI Medical Informatics and Artificial Intelligence
#OpenAccess 💡
"Consumer perspectives on the national electronic health record and barriers to its adoption in Germany: Does health policy require a change in communication?"

German #ePA | #Adoption #Communication #Expectations

bmchealthservres.biomedcentral.com/articles/10....
Consumer perspectives on the national electronic health record and barriers to its adoption in Germany: does health policy require a change in communication? - BMC Health Services Research
Background The national health record (ePA) was introduced January 1st, 2021 in Germany and is available to every person insured under statutory health insurance. This study investigated the acceptanc...
bmchealthservres.biomedcentral.com
January 7, 2025 at 9:06 AM
Reposted by MIKI Medical Informatics and Artificial Intelligence
#JustPublished collab study by D Müller et al on “Assessing Patient Health Dynamics by Comparative CT Analysis: An Automatic Approach to Organ and Body Feature Evaluation” in MDPI Diagnostics
@uni-kiel.de @hannesulrich.bsky.social @bschreiweis.bsky.social #mi #mii

www.mdpi.com/2075-4418/14...
Assessing Patient Health Dynamics by Comparative CT Analysis: An Automatic Approach to Organ and Body Feature Evaluation
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 ...
www.mdpi.com
December 10, 2024 at 3:39 PM
#JustPublished collab study by D Müller et al on “Assessing Patient Health Dynamics by Comparative CT Analysis: An Automatic Approach to Organ and Body Feature Evaluation” in MDPI Diagnostics
@uni-kiel.de @hannesulrich.bsky.social @bschreiweis.bsky.social #mi #mii

www.mdpi.com/2075-4418/14...
Assessing Patient Health Dynamics by Comparative CT Analysis: An Automatic Approach to Organ and Body Feature Evaluation
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 ...
www.mdpi.com
December 10, 2024 at 3:39 PM
Reposted by MIKI Medical Informatics and Artificial Intelligence
#justPublished Neue Publikation zu den #DIZ der #MII und des NUM von Albashiti et al im Bundesgesundheitsblatt https://rdcu.be/dFPFi
April 26, 2024 at 7:29 AM