Oya Beyan
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View article: Canadian Inborn Errors of Immunity National Registry (CIEINR): A High-Quality Standardized Patient Data Platform to Support Patient Advocacy and Immune Deficiency Research
Canadian Inborn Errors of Immunity National Registry (CIEINR): A High-Quality Standardized Patient Data Platform to Support Patient Advocacy and Immune Deficiency Research Open
Introduction Inborn errors of immunity (IEIs) comprise a heterogeneous group of rare disorders, characterized by a wide spectrum of immunological alterations that influence the presentation and age at onset of disease. Approximately 30,000…
View article: Catnip for MedCAT: Optimizing the Input for Automated SNOMED CT Mapping of Clinical Variables
Catnip for MedCAT: Optimizing the Input for Automated SNOMED CT Mapping of Clinical Variables Open
Introduction: Mapping local medical data assets to international data standards such as medical ontology SNOMED CT fosters data harmonization and, thereby, global progress in medical research. Since its intense resource requirements often …
View article: Implementation of HL7 FHIR-Based Terminology Services for a National Federated Health Research Infrastructure
Implementation of HL7 FHIR-Based Terminology Services for a National Federated Health Research Infrastructure Open
Introduction: As part of the German Medical Informatics Initiative (MII) and Network University Medicine (NUM), a central research terminology service (TS) is provided by the Service Unit Terminology Services (SU-TermServ). This HL7 FHIR-b…
View article: From Normal to Optimal: Investigating Metabolic and Inflammatory Parameters as Predictors of Survival in Locally Advanced Cervical Cancer
From Normal to Optimal: Investigating Metabolic and Inflammatory Parameters as Predictors of Survival in Locally Advanced Cervical Cancer Open
Cervical cancer is the third most common cancer in women, and recent studies have highlighted the importance of body composition markers in predicting patient outcomes. We build upon the data of 83 patients from the Uterus-11 study, to exp…
View article: Real-Time Automated Monitoring Architecture for Ensuring Quality ETL Processes in Healthcare Data: A Case Study from Cologne University Hospital’s Medical Data Integration Center
Real-Time Automated Monitoring Architecture for Ensuring Quality ETL Processes in Healthcare Data: A Case Study from Cologne University Hospital’s Medical Data Integration Center Open
This case study discusses the effectiveness of implementing a real-time automated monitoring architecture using the ELK Stack (Elasticsearch, Logstash and Kibana) to ensure data ingestion quality within the Medical Data Integration Center …
View article: Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability
Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability Open
Summary While Research Electronic Data Capture (REDCap) has been widely adopted in rare disease research, its unconstrained data format often leads to implementations that lack native interoperability with global health data standards, lim…
View article: EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning
EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning Open
Recent advances in reinforcement learning (RL) for large language model (LLM) fine-tuning show promise in addressing multi-objective tasks but still face significant challenges, including competing objective balancing, low training efficie…
View article: FDO Manager: Minimum Viable FAIR Digital Object Implementation
FDO Manager: Minimum Viable FAIR Digital Object Implementation Open
In the digital age, data has emerged as one of the most valuable assets across various sectors, including academia, industry, and healthcare. Effective data preservation involves the management of data to ensure its long-term accessibility…
View article: An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets
An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets Open
Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructu…
View article: Challenges of Entrepreneurship Teaching in the Healthtech and Medtech Domains
Challenges of Entrepreneurship Teaching in the Healthtech and Medtech Domains Open
The rapidly evolving landscapes of healthtech and medtech present unique challenges for entrepreneurship education, necessitating a specialized pedagogical approach. This paper explores pedagogical frameworks and the multifaceted barriers …
View article: Semi-Automatic Export of Electrophysiological Metadata to NFDI4Health Local Data Hubs: Use Case of Microneurography odML-Tables – A Technical Case Report
Semi-Automatic Export of Electrophysiological Metadata to NFDI4Health Local Data Hubs: Use Case of Microneurography odML-Tables – A Technical Case Report Open
Introduction: The Local Data Hub (LDH) is a platform for FAIR sharing of medical research (meta-)data. In order to promote the usage of LDH in different research communities, it is important to understand the domain-specific needs, solutio…
View article: Early Multimodal Data Integration for Data-Driven Medical Research – A Scoping Review
Early Multimodal Data Integration for Data-Driven Medical Research – A Scoping Review Open
Introduction: Data-driven medical research (DDMR) needs multimodal data (MMD) to sufficiently capture the complexity of clinical cases. Methods for early multimodal data integration (MMDI), i.e. integration of the data before performing a …
View article: Seeing the primary tumor because of all the trees: Cancer type prediction on low-dimensional data
Seeing the primary tumor because of all the trees: Cancer type prediction on low-dimensional data Open
The Cancer of Unknown Primary (CUP) syndrome is characterized by identifiable metastases while the primary tumor remains hidden. In recent years, various data-driven approaches have been suggested to predict the location of the primary tum…
View article: How Data Infrastructure Deals with Bias Problems in Medical Imaging
How Data Infrastructure Deals with Bias Problems in Medical Imaging Open
The paper discusses biases in medical imaging analysis, particularly focusing on the challenges posed by the development of machine learning algorithms and generative models. It introduces a taxonomy of bias problems and addresses them thr…
View article: Review of Key Elements in Developing a Common Data Model for Rare Diseases: Identifying Common Success Factors
Review of Key Elements in Developing a Common Data Model for Rare Diseases: Identifying Common Success Factors Open
This paper explores key success factors for the development and implementation of a Common Data Model (CDM) for Rare Diseases (RDs) focusing on the European context. Several challenges hinder RD care and research in diagnosis, treatment, a…
View article: Harmonizing Microneurography Metadata with Local Data Hubs: A Concept
Harmonizing Microneurography Metadata with Local Data Hubs: A Concept Open
This work aims to improve FAIR-ness of the microneurography research by integrating the local (meta)data to existing research data infrastructures. In the previous work, we developed an odML based solution for local metadata storage of mic…
View article: Data Quality in Medical Real-World Data – An Oncological Use Case
Data Quality in Medical Real-World Data – An Oncological Use Case Open
Data quality deficiencies significantly limit the applicability of real-world data in data-driven medical research. In this study, using an oncological use case, we report and discuss common quality deficiencies in real-world medical datas…
View article: Cybersecurity Frameworks in Healthcare Data: Short Literature Review
Cybersecurity Frameworks in Healthcare Data: Short Literature Review Open
The importance of cybersecurity in healthcare, with a focus on safeguarding sensitive patient information from unauthorized access, use, or disclosure, cannot be overstated Security breaches in this sector can have significant consequences…
View article: Real-Time Visualization and Analysis Architecture for Data Integration Processes at Cologne University Hospital’s Medical Data Integration Center
Real-Time Visualization and Analysis Architecture for Data Integration Processes at Cologne University Hospital’s Medical Data Integration Center Open
This paper presents an implementation of an architecture based on open-source solutions using ELK Stack – Elasticsearch, Logstash, and Kibana – for real-time data analysis and visualizations in the Medical Data Integration Center, Universi…
View article: Towards an ELSA Curriculum for Data Scientists
Towards an ELSA Curriculum for Data Scientists Open
The use of artificial intelligence (AI) applications in a growing number of domains in recent years has put into focus the ethical, legal, and societal aspects (ELSA) of these technologies and the relevant challenges they pose. In this pap…
View article: Identification of Medical Ecosystems in the Field of Mental Health and Cardiovascular Diseases at the Cologne Site
Identification of Medical Ecosystems in the Field of Mental Health and Cardiovascular Diseases at the Cologne Site Open
As part of the Europe-wide smart health innovation hub implemented in the context of the Horizon Europe SHIFT-HUB project, our work concerns the identification of specific medical research ecosystems in the two fields, namely cardiovascula…
View article: FDO Manager: Minimum Viable FAIR Digital Object Implementation
FDO Manager: Minimum Viable FAIR Digital Object Implementation Open
In the digital age, data has emerged as one of the most valuable assets across various sectors, including academia, industry, and healthcare. Effective data preservation involves the management of data to ensure its long-term accessibility…
View article: Voxel-Wise Medical Image Generalization for Eliminating Distribution Shift
Voxel-Wise Medical Image Generalization for Eliminating Distribution Shift Open
Currently, the medical field is witnessing an increase in the use of machine learning techniques. Supervised learning methods adopted in classification, prediction, and segmentation tasks for medical images always experience decreased perf…
View article: Will it run?—A proof of concept for smoke testing decentralized data analytics experiments
Will it run?—A proof of concept for smoke testing decentralized data analytics experiments Open
The growing interest in data-driven medicine, in conjunction with the formation of initiatives such as the European Health Data Space (EHDS) has demonstrated the need for methodologies that are capable of facilitating privacy-preserving da…
View article: Towards an ELSA Curriculum for Data Scientists
Towards an ELSA Curriculum for Data Scientists Open
The use of Artificial Intelligence (AI) applications in a growing number of domains in the latest years has put into focus Ethical Legal and Societal Aspects (ELSA) of these technologies and the relevant challenges they pose. In this paper…
View article: Stakeholders of Cardiovascular Innovation Ecosystems in Germany
Stakeholders of Cardiovascular Innovation Ecosystems in Germany Open
This paper aims to provide a first attempt towards analysis innovation ecosystems for cardiovascular pathologies in Germany through the use of a stakeholder model. We present essential stakeholders for the development and deployment of inn…
View article: From Large Language Models to Knowledge Graphs for Biomarker Discovery in Cancer
From Large Language Models to Knowledge Graphs for Biomarker Discovery in Cancer Open
Domain experts often rely on most recent knowledge for apprehending and disseminating specific biological processes that help them design strategies for developing prevention and therapeutic decision-making in various disease scenarios. A …
View article: Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy
Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy Open
We designed an end-to-end pipeline for glomerular Oxford Classification on both a granular glomerular and an entire biopsy level. Both the glomerular segmentation and the classification modules are freely available for further development …