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  1. Book ; Online ; Conference proceedings: German Medical Data Sciences 2023 - Science. Close to the people

    Zapf, Antonia / Röhrig, Rainer / Grabe, Nils / Haag, Martin / Hübner, Ursula / Sax, Ulrich / Schmidt, Carsten / Sedlmayr, Martin

    Proceedings of the 68th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2023

    (Studies in health technology and informatics ; 307)

    2023  

    Title variant Science. Close to the people ; German medical data sciences
    Event/congress Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (68., 2023, Heilbronn, Jahrestagung)
    Author's details editors: Rainer Röhrig, Nils Grabe, Martin Haag, Ursula Hübner, Ulrich Sax, Carsten Oliver Schmidt, Martin Sedlmayr, Antonia Zapf
    Series title Studies in health technology and informatics ; 307
    Collection
    Language English
    Size 1 Online-Ressource (xvi, 288 Seiten), Illustrationen, Diagramme
    Publisher IOS Press
    Publishing place Amsterdam
    Publishing country Germany
    Document type Book ; Online ; Conference proceedings
    Note Kostenfreier Zugang nach Registrierung ; Open Access
    HBZ-ID HT030621504
    ISBN 978-1-64368-429-1 ; 9781643684284 ; 1-64368-429-9 ; 1643684280
    DOI 10.3233/SHTI307
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Thesis: Die Verbreitung und Charakterisierung von Rückenschmerzen in der deutschen Erwachsenenbevölkerung

    Schmidt, Carsten

    2011  

    Author's details vorgelegt von Carsten Oliver Schmidt
    Language German
    Size 105 S. : graph. Darst.
    Publishing country Germany
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Greifswald, Univ., Habil.-Schr., 2011
    Note Enth. 5 Sonderabdr. aus verschiedenen Zeitschr.
    HBZ-ID HT017753366
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2013 E 826 order for loan Magazin

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  3. Book ; Online: Training concepts in research data management and data science with the focus on health research

    Dierkes, Jens / Fürst, Julia / Hörner, Tanja / Klammt, Georg Sebastian / Lindstädt, Birte / Pigeot, Iris / Restel, Katja / Schmidt, Carsten / Waltemath, Dagmar / Zeleke, Atinkut Alamirrew

    2023  

    Abstract: The digital transformation taking place across all sectors and the associated increase in the importance of research data in gaining knowledge or innovating new technologies poses enormous challenges for the workforce, policy makers, funders, educational ...

    Institution NFDI4Health - Nationale Forschungsdateninfrastruktur für personenbezogene Gesundheitsdaten
    Deutsche Forschungsgemeinschaft
    Author's details Jens Dierkes, Julia Fürst, Tanja Hörner, Sebastian Klammt, Birte Lindstädt, Iris Pigeot, Katja Restel, Carsten Oliver Schmidt, Dagmar Waltemath, Atinkut Zeleke for NFDI4Health ; NFDI4Health has received funding from the Deutsche Forschungsgemeinschaft (DFG) ; design, setting, layout: Alina Esken ; language editing: Andrew Rennison
    Abstract The digital transformation taking place across all sectors and the associated increase in the importance of research data in gaining knowledge or innovating new technologies poses enormous challenges for the workforce, policy makers, funders, educational institutions, etc. In particular, it is essential to equip everyone with the skills or skill sets that are required (i) to handle the many facets of data, (ii) to understand their various constraints, (iii) to be able to make informed decisions about the appropriate use of available technologies, and (iv) to gain "wisdom" from the data. It is therefore crucial to start teaching basic skills while at school and to deepen them as early as possible, e.g. in academic training programmes. The field of data literacy tackles these issues and is an attempt to systematise tasks and corresponding skills by way of one or more frameworks. According to Ridsdale et al. (2015), "Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner."
    Subject code 001 ; 004 ; 610
    Language English
    Size 1 Online-Ressource (97 Seiten), Diagramme
    Publisher NFDI4Health
    Publishing place Cologne
    Publishing country Germany
    Document type Book ; Online
    Note This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) ; NFDI4Health has received funding from the Deutsche Forschungsgemeinschaft (DFG) under Grant Agreement no. 442326535. Data Train is supported by the U Bremen Research Alliance and the Federal State of Bremen. ; Open Access
    HBZ-ID HT030065245
    Database Repository for Life Sciences

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  4. Book ; Online: Informed consent zum record linkage

    Intemann, Timm / Lettieri, Vanessa / Kipker, Dennis-Kenji / Kuntz, Alessandra / Ahrens, Wolfgang / Pigeot, Iris / Buchner, Benedikt / Sax, Ulrich / Fluck, Juliane / Fröhlich, Holger / Geok Ng, Hwei / Hahn, Horst K. / Kirsten, Toralf / Lange, Johann-Jesko / Lassen-Schmidt, Bianca / Prause, Guido / Richter, Adrian / Schmidt, Carsten

    best practice und Mustertexte

    2023  

    Abstract: Ausgangssituation: Die informierte Einwilligung ("Informed Consent") stellt den Königsweg für die Nutzung personenbezogener Daten dar. Gute Beispiele und Orientierungshilfen sind z.B. bei der Deutsche Gesellschaft für Medizinische Informatik, Biometrie ... ...

    Institution NFDI4Health - Nationale Forschungsdateninfrastruktur für personenbezogene Gesundheitsdaten
    Author's details NFDI4Health Task Force COVID-19 ; Autoren: Intemann, Timm; Lettieri, Vanessa; Kipker, Dennis-Kenji; Kuntz, Alessandra; Ahrens, Wolfgang; Pigeot, Iris; Buchner, Benedikt; Sax, Ulrich; im Namen des NFDI4Health Konsortiums und der NFDI4Health Task Force COVID-19 ; Projektmitglieder: Fluck, Juliane; Fröhlich, Holger; Geok Ng, Hwei; Hahn, Horst; Kirsten, Toralf; Lange, Johann-Jesko; Lassen-Schmidt, Bianca; Prause, Guido; Richter, Adrian; Schmidt, Carsten
    Abstract Ausgangssituation: Die informierte Einwilligung ("Informed Consent") stellt den Königsweg für die Nutzung personenbezogener Daten dar. Gute Beispiele und Orientierungshilfen sind z.B. bei der Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS) bzw. der Medizininformatik Initiative (MII) zu finden. Für die prospektive Verknüpfung eines personenbezogenen Datensatzes mit weiteren personenbezogenen Daten (Record Linkage) – z.B. die Anreicherung von Primärdaten einer epidemiologischen Studie mit Sekundärdaten aus der Krankenversorgung bzw. von Kostenträgern – gestaltet sich das Vorgehen hinsichtlich der Datenschutzanforderungen als sehr komplex. Studien in der Onkologie bzw. der Infektionsforschung, bei meldepflichtigen Erkrankungen bzw. im COVID-19-Umfeld könnten als Erlaubnistatbestand das jeweilige Krebsregistergesetz bzw. das Infektionsschutzgesetz heranziehen. Epidemiologische Studien erfordern i.d.R. diesbezüglich einen Informed Consent zum Record Linkage. Es kann allerdings nicht davon ausgegangen werden, dass alle Betroffenen diesen Informed Consent dazu uneingeschränkt erteilen. Zudem kann eine solche Einwilligung widerrufen werden. Aufgrund der sich daraus ergebenden Anforderungen werden für zukünftige Projekte Mustertexte für die informierte Einwilligung zum Record Linkage als Grundlage für studienspezifische Einwilligungserklärungen – nicht nur für COVID-19 – bereitgestellt. Diese basieren auf erprobten Aufklärungstexten und Formulierungen aus der CoVerlauf-Studie sowie der NAKO Gesundheitsstudie.
    Keywords COVID-19
    Subject Coronavirus-Krankheit-2019 ; Corona virus disease 2019 ; Coronavirus disease 2019 ; 2019-nCoV acute respiratory disease ; Wuhan pneumonia ; COVID-19-Infektion ; Coronavirus-SARS-CoV-2-Infektion ; SARS-CoV-2-Infektion
    Subject code 004
    Language German
    Size 1 Online-Ressource (15 Seiten, 16 ungezählte Seiten), Illustrationen
    Edition Version: V1_1
    Publisher NFDI4Health Task Force COVID-19
    Publishing place Köln
    Publishing country Germany
    Document type Book ; Online
    Note Dieses Werk ist lizensiert unter einer Creative Commons Namensnennung 4.0 International Lizenz (https://creativecommons.org/licenses/by/4.0/) ; Open Access
    HBZ-ID HT021716400
    DOI 10.4126/FRL01-006399943
    Database Repository for Life Sciences

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  5. Article ; Online: Chronic pain is associated with less grey matter volume in the anterior cingulum, anterior and posterior insula and hippocampus across three different chronic pain conditions.

    Neumann, Nicola / Domin, Martin / Schmidt, Carsten-Oliver / Lotze, Martin

    European journal of pain (London, England)

    2023  Volume 27, Issue 10, Page(s) 1239–1248

    Abstract: Background: Chronic pain of different aetiologies and localization has been associated with less grey matter volume (GMV) in several cortical and subcortical brain areas. Recent meta-analyses reported low reproducibility of GMV alterations between ... ...

    Abstract Background: Chronic pain of different aetiologies and localization has been associated with less grey matter volume (GMV) in several cortical and subcortical brain areas. Recent meta-analyses reported low reproducibility of GMV alterations between studies and pain syndromes.
    Methods: To investigate GMV in common chronic pain conditions defined by body location (chronic back pain, n = 174; migraine, n = 92; craniomandibular disorder, n = 39) compared to controls (n = 296), we conducted voxel-based morphometry and determined GMV from high-resolution cranial MRIs obtained in an epidemiologic survey. Mediation analyses were performed between the presence of chronic pain and GMV testing the mediators stress and mild depression. The predictability of chronic pain was investigated with binomial logistic regression.
    Results: Whole-brain analyses yielded reduced GMV within the left anterior insula and the anterior cingulate cortex, for a ROI approach additionally the left posterior insula and left hippocampus showing less GMV across all patients with chronic pain. The relationship of pain with GMV in the left hippocampus was mediated by self-reported stressors in the last 12 months. Binomial logistic regression revealed a predictive effect for GMV in the left hippocampus and left anterior insula/temporal pole for the presence of chronic pain.
    Conclusions: Chronic pain across three different pain conditions was characterized by less GMV in brain regions consistently described for different chronic pain conditions before. Less GMV in the left hippocampus mediated by experienced stress during the last year might be related to altered pain learning mechanisms in chronic pain patients.
    Significance: Grey matter reorganization could serve as a diagnostic biomarker for chronic pain. In a large cohort, we here replicated findings of less grey matter volume across three pain conditions in the left anterior and posterior insula, anterior cingulate and left hippocampus. Less hippocampal grey matter was mediated by experienced stress.
    Language English
    Publishing date 2023-06-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 1390424-3
    ISSN 1532-2149 ; 1090-3801
    ISSN (online) 1532-2149
    ISSN 1090-3801
    DOI 10.1002/ejp.2153
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 5194: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: Bringing Communities Together: Mapping the Investigation-Study-Assay-Model (ISA) to Fast Healthcare Interoperability Resources (FHIR).

    Klopfenstein, Sophie A I / Sass, Julian / Vorisek, Carina N / Jorczik, Felix / Schmidt, Carsten Oliver / Löbe, Matthias / Golebiewski, Martin / Abaza, Haitham / Thun, Sylvia

    Studies in health technology and informatics

    2024  Volume 310, Page(s) 18–22

    Abstract: Adhering to FAIR principles (findability, accessibility, interoperability, reusability) ensures sustainability and reliable exchange of data and metadata. Research communities need common infrastructures and information models to collect, store, manage ... ...

    Abstract Adhering to FAIR principles (findability, accessibility, interoperability, reusability) ensures sustainability and reliable exchange of data and metadata. Research communities need common infrastructures and information models to collect, store, manage and work with data and metadata. The German initiative NFDI4Health created a metadata schema and an infrastructure integrating existing platforms based on different information models and standards. To ensure system compatibility and enhance data integration possibilities, we mapped the Investigation-Study-Assay (ISA) model to Fast Healthcare Interoperability Resources (FHIR). We present the mapping in FHIR logical models, a resulting FHIR resources' network and challenges that we encountered. Challenges mainly related to ISA's genericness, and to different structures and datatypes used in ISA and FHIR. Mapping ISA to FHIR is feasible but requires further analyses of example data and adaptations to better specify target FHIR elements, and enable possible automatized conversions from ISA to FHIR.
    MeSH term(s) Humans ; Drugs, Generic ; Health Facilities ; Metadata ; Delivery of Health Care
    Chemical Substances Drugs, Generic
    Language English
    Publishing date 2024-01-25
    Publishing country Netherlands
    Document type Journal Article
    ISSN 1879-8365
    ISSN (online) 1879-8365
    DOI 10.3233/SHTI230919
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Conference proceedings: An improved metadata schema to support data quality reporting in R

    Mariño, Joany / Kasbohm, Elisa / Struckmann, Stephan / Schmidt, Carsten Oliver

    2023  , Page(s) Abstr. 233

    Event/congress 68. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS); Heilbronn; Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie; 2023
    Keywords Medizin, Gesundheit ; metadata ; data quality ; FAIRness
    Publishing date 2023-09-15
    Publisher German Medical Science GMS Publishing House; Düsseldorf
    Document type Conference proceedings
    DOI 10.3205/23gmds083
    Database German Medical Science

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  8. Conference proceedings: dataquieR 2.0 — Improved Functionality for Data Quality Reporting

    Struckmann, Stephan / Mariño, Joany / Kasbohm, Elisa / Schmidt, Carsten Oliver

    2023  , Page(s) Abstr. 153

    Event/congress 68. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS); Heilbronn; Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie; 2023
    Keywords Medizin, Gesundheit ; data quality analysis ; metadata ; FAIRness ; standards
    Publishing date 2023-09-15
    Publisher German Medical Science GMS Publishing House; Düsseldorf
    Document type Conference proceedings
    DOI 10.3205/23gmds082
    Database German Medical Science

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  9. Conference proceedings: Modularised Programming to Reduce Complexity and Enhance Reusability in Data Quality Assessments

    Struckmann, Stephan / Henke, Jörg / Schmidt, Carsten Oliver

    2022  , Page(s) Abstr. 159

    Event/congress 67. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS), 13. Jahreskongress der Technologie- und Methodenplattform für die vernetzte medizinische Forschung e.V. (TMF); sine loco [digital]; Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie; 2022
    Keywords Medizin, Gesundheit ; data quality ; database ; data dictionary ; programming ; pipeline
    Publishing date 2022-08-19
    Publisher German Medical Science GMS Publishing House; Düsseldorf
    Document type Conference proceedings
    DOI 10.3205/22gmds017
    Database German Medical Science

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  10. Article ; Online: Predicting Physician Consultations for Low Back Pain Using Claims Data and Population-Based Cohort Data-An Interpretable Machine Learning Approach.

    Richter, Adrian / Truthmann, Julia / Chenot, Jean-François / Schmidt, Carsten Oliver

    International journal of environmental research and public health

    2021  Volume 18, Issue 22

    Abstract: 1) Background: Predicting chronic low back pain (LBP) is of clinical and economic interest as LBP leads to disabilities and health service utilization. This study aims to build a competitive and interpretable prediction model; (2) Methods: We used ... ...

    Abstract (1) Background: Predicting chronic low back pain (LBP) is of clinical and economic interest as LBP leads to disabilities and health service utilization. This study aims to build a competitive and interpretable prediction model; (2) Methods: We used clinical and claims data of 3837 participants of a population-based cohort study to predict future LBP consultations (ICD-10: M40.XX-M54.XX). Best subset selection (BSS) was applied in repeated random samples of training data (75% of data); scoring rules were used to identify the best subset of predictors. The rediction accuracy of BSS was compared to
    MeSH term(s) Cohort Studies ; Humans ; Low Back Pain/epidemiology ; Machine Learning ; Physicians ; Referral and Consultation
    Language English
    Publishing date 2021-11-16
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2175195-X
    ISSN 1660-4601 ; 1661-7827
    ISSN (online) 1660-4601
    ISSN 1661-7827
    DOI 10.3390/ijerph182212013
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