A5077603419- Biomedical Text Mining and Ontologies
- Research Data Management Practices
- Scientific Computing and Data Management
- Data Quality and Management
- Semantic Web and Ontologies
- Academic Publishing and Open Access
- Bioinformatics and Genomic Networks
- Data-Driven Disease Surveillance
- Asymmetric Hydrogenation and Catalysis
- Health and Medical Studies
- Computational Drug Discovery Methods
- COVID-19 diagnosis using AI
- Natural Language Processing Techniques
- Chronic Disease Management Strategies
- Topic Modeling
- Ethics in Clinical Research
- Genomics and Rare Diseases
- Medical and Health Sciences Research
- Misinformation and Its Impacts
- Machine Learning in Bioinformatics
ZB MED - Information Centre for Life Sciences
2021-2024
Fraunhofer Institute for Algorithms and Scientific Computing
2018-2020
Abstract Motivation The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well data description, linking and harmonization in context of COVID-19, we have developed ontology representing major novel coronavirus (SARS-CoV-2) entities. a strong scope on chemical entities suited for drug repurposing, this is target ongoing therapeutic development. Results comprises 2270 classes concepts 38 987 axioms (2622...
Abstract FAIRification of personal health data is utmost importance to improve research and political as well medical decision-making, which ultimately contributes a better the general population. Despite many advances in information technology, several obstacles such interoperability problems remain relevant on topic interest likely be missed out due time-consuming search access processes. A recent example COVID-19 pandemic, where understanding virus’ transmission dynamics preventive...
For all research data collected, descriptions and information about the corresponding variables are essential for analysis reuse. To enable cross-study comparisons analyses, semantic interoperability of metadata is one most important requirements. In area clinical epidemiological studies, collection instruments such as case report forms (CRFs), dictionaries questionnaires critical collection. Even though often created in a digital form, they mostly not machine readable; i.e., semantically...
Abstract preVIEW is a freely available semantic search engine for Coronavirus disease (COVID-19)-related preprint publications. Currently, it contains >43 800 documents indexed with >4000 concepts, annotated automatically. During the last 2 years, dynamic situation of corona crisis has demanded development. Whereas new concepts have been added over time—such as severe acute respiratory syndrome coronavirus (SARS-CoV-2) variants interest—the service also extended several...

 The current COVID-19 pandemic emphasizes the use of so-called preprints - a type publication that is not subject to peer review. Due its global relevance, there an immense number COVID-19-related every day. To help researchers find relevant information, we have developed semantic search engine preVIEW, it integrates from currently seven different preprint servers. For indexing, implemented various text mining components tag, for example, diseases or SARS-CoV-2 specific proteins. While...
In this paper we suggest a novel systematization of Information Retrieval and Natural Language Processing problems.Using rather general description problems are able to discuss proof the equivalence some problems.We provide reformulations well-known like Named Entity Recognition using our further research expected outcome.We will relation two problems, cluster labeling search query finding.With these results optimization approach both problems.This provides yet unknown view generating new...
Abstract Motivation Epilepsy is a multifaceted complex disorder that requires precise understanding of the classification, diagnosis, treatment and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive structured knowledge missing. In contemplation to promote multidisciplinary exchange facilitate advancement in clinical management, especially pre-clinical research, disease-specific ontology necessary. The presented designed enable better...
The German Central Health Study Hub COVID-19 is an online service that offers bundled access to related studies conducted in Germany. It combines metadata and other information of epidemiologic, public health clinical into a single data repository for FAIR access. In addition study characteristics the system also allows easy documents, as well instruments collection. survey are decomposed individual items semantically enriched ease findability. Data from existing trial registries (DRKS,...
COVID-19 posed one of the greatest challenges to individuals and societies worldwide in recent decades. Public health research, epidemiological clinical studies were essential track spread SARS-CoV-2 responsible for pandemic its variants, better understand consequences social life, identify effective treatment vaccination methods. Such provided policy makers, industry, care providers, society with an empirical basis containing managing making decisions that based on most data. Therefore,...
doch erfullen Studienprotokolle, eingesetzte Erhebungsinstrumente und erhobene Daten die Anforderungen der FAIR-Prinzipien nicht in ausreichendem Mase. NFDI4Health wird daher eine Struktur schaffen, zentrale Suche nach existierenden, dezentral verwalteten Datenkorpern zugehorigen Dokumenten sowie einen FAIRen Zugang zu diesen erleichtert. Dazu werden Auffindbarkeit strukturierten Gesundheitsdaten aus Registern, administrativen Gesundheitsdatenbanken, klinischen epidemiologischen Public...
<sec> <title>BACKGROUND</title> Despite wide acceptance in medical research, implementation of the FAIR principles (Findability, Accessibility, Interoperability, Reusability) is lacking certain health domains and interoperability across data sources remains a challenge. While clinical trial registries collect metadata about studies, numerous epidemiological public studies examining chronic disease burden remain unregistered or missing detailed information relevant study documents. Making...
Introduction: The German Central Health Study Hub is a service that was initially developed at short notice during the COVID-19 pandemic. Since then, it has been expanded in scope, content, active users and functionality. aimed two main audiences: data provider consumers. former want to share research from clinical, public health epidemiological studies related documents according FAIR criteria for data, latter find ultimately reuse relevant above areas. Methods: connects both groups via...
Health data collected in clinical trials and epidemiological as well public health studies cannot be freely published, but are valuable datasets whose subsequent use is of high importance for research. The National Research Data Infrastructure Personal (NFDI4Health) aims to promote the publication such without compromising privacy. Based on existing international standards, NFDI4Health has established a generic information model description preservation high-level metadata describing...
Abstract Motivation: Epilepsy is a multi-faceted complex disorder that requires precise understanding of the classification, diagnosis, treatment, and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive structured knowledge missing. In contemplation to promote multidisciplinary exchange facilitate advancement in clinical management, especially pre-clinical research, disease-specific ontology necessary. The presented designed enable better...