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Auflistung nach Autor:in "Sedlmayr, Martin"

1 - 7 von 7
  • Konferenzbeitrag
    Air Quality Portals - Designing Citizen-centred Supply Chains for the Dissemination of Air Quality Information
    (Environmental Communication in the Information Society - Proceedings of the 16th Conference, 2002) Peinel, Gertraud; Rose, Thomas; Sedlmayr, Martin
    Environmental information represents an attractive business asset once perceived as levels of comfort improving the daily life of citizens. The need for high-quality information services is further supported by several European directives to inform the citizen about environmental conditions as well as ongoing initiatives concerning access, dissemination and exploitation of public sector information (PSI). Although elementary publishing services are available, e.g. web servers on air quality, the question arises of how to reach and eventually impact the citizen with information on air quality and how to establish sustainable supply chains for environmental content. In this paper, we will present the air quality portals designed and evaluated in project APNEE and APNEE-TU which implement citizen-centred information services by employing a complementary array of technologies in a customised fashion. Operation of these information services requires a specific business partnership to implement a supply chain of trusted content from the source of environmental information, i.e. the environmental management systems, to the citizen, i.e. the customer of high-quality content. This paper reports on the innovative design of the service platform for pro-active content dissemination, as well as stakeholders and business perspectives for a sustainable operation of APNEE/APNEE-TU.
  • Konferenzbeitrag
    Ansatz und Risikoanalyse für ein Smart Object Network im Krankenhaus
    (Informatik 2009 – Im Focus das Leben, 2009) Sedlmayr, Martin; Becker, Andreas; Münch, Ulli; Meier, Fritz; Prokosch, Hans-Ulrich; Ganslandt, Thomas
  • Zeitschriftenartikel
    Editorial
    (it - Information Technology: Vol. 61, No. 5-6, 2019) Schlieter, Hannes; Sunyaev, Ali; Breitschwerdt, Rüdiger; Sedlmayr, Martin
    Article Editorial was published on October 1, 2019 in the journal it - Information Technology (volume 61, issue 5-6).
  • Konferenzbeitrag
    Environmental Services and Data Brokerage Portal: ENV-e-CITY in Action
    (The Information Society and Enlargement of the European Union, 2003) Moussiopoulos, Nicolas; Karatzas, Kostas; Endregard, Geir; Fedra, Kurt; Friedrich, Rainer; Johansen, Per Henrik; Kalognomou, Liana; Karppinen, Ari; Kraggerud, Per Haavard; Kukkonen, Jaakko; Larssen, Steinar; de Leeuw, Frank; Lohmeyer, Achim; Naneris, Chris; Nicklass, Daniel; Papaioannou, Giannis; Peinel, Gertraud; Pulles, Tinus; Reis, Stefan; Rose, Thomas; Sedlmayr, Martin; van den Hout, Dick
    ENV-e-CITY is a European Commission supported e-content project that aims to develop an internet-based service for environmental information related applications. The motivation of this project lies in the need of European cities to perform assessments for complying with the EU environmental legislation, as well as the requirement for efficient environmental impact assessments. The e-content domain considered extends over four environmental application areas: air emission, air quality, topography, and meteorology. The application framework includes meta-data structures for these domains, export and import filters, interfaces and typical e-content services. The user community of the platform envisaged consists of city authorities, consultants involved in environmental impact assessment studies as well as citizens desiring valid information on the state of the atmospheric environment. An initial set of electronic information services is currently under development and will be demonstrated on the basis of the various user categories.
  • Zeitschriftenartikel
    Exploiting Latent Embeddings of Nominal Clinical Data for Predicting Hospital Readmission
    (KI - Künstliche Intelligenz: Vol. 29, No. 2, 2015) Krompaß, Denis; Esteban, Cristóbal; Tresp, Volker; Sedlmayr, Martin; Ganslandt, Thomas
    Hospital readmissions of patients put a high burden not only on the health care system, but also on the patients since complications after discharge generally lead to additional burdens. Estimating the risk of readmission after discharge from inpatient care has been the subject of several publications in recent years. In those publications the authors mostly tried to directly infer the readmission risk (within a certain time frame) from the clinical data recorded in the medical routine such as primary diagnosis, co-morbidities, length of stay, or questionnaires. Instead of using these data directly as inputs for a prediction model, we are exploiting latent embeddings for the nominal parts of the data (e.g., diagnosis and procedure codes). These latent embeddings have been used with great success in the natural language processing domain and can be constructed in a preprocessing step. We show in our experiments, that a prediction model that exploits these latent embeddings can lead to improved readmission predictive models.
  • Zeitschriftenartikel
    Multi-Case-Studie zu Barrieren und förderlichen Faktoren der digitalen Kompetenz von Patienten – Ein interdisziplinärer Ansatz
    (HMD Praxis der Wirtschaftsinformatik: Vol. 61, No. 1, 2024) Kählig, Maren; Susky, Marcel; Hickmann, Emily; Grummt, Sophia; Richter, Daniela; Richter, Peggy; Weidner, Jens; Sedlmayr, Martin; Seim, Anne
    Die rasanten Fortschritte digitaler Technologien haben die Gesundheitsversorgung revolutioniert und dabei unter anderem die Vernetzung von Patienten, Gesundheitsdienstleistenden, Entwicklern und Forschenden in den Mittelpunkt gerückt. Um das volle Potenzial dieser Transformation auszuschöpfen, ist es von entscheidender Bedeutung, die digitalen Kompetenzen der Patienten und des medizinischen Fachpersonals zu fördern. Besonders vor dem Hintergrund des demografischen Wandels wird das Verständnis und die Anwendung digitaler Innovationen in der Gesundheitsversorgung zu einer Schlüsselaufgabe. Unsere Forschungsarbeit konzentrierte sich daher auf eine Multi-Case-Studie im Rahmen des „Medical Informatics Hub for Saxony“, um die für die erfolgreiche Nutzung digitaler Gesundheitstechnologien benötigten digitalen Kompetenzen von Patienten zu identifizieren. Um einen strategischen Ansatz für den Aufbau dieser Fähigkeiten entwickeln zu können, untersuchten wir zudem Einflussfaktoren auf diese Kompetenzen. Die Ergebnisse unserer Studie verdeutlichen, dass die Digitalisierung zwar bereits im Alltag der Patienten präsent ist, Bedenken hinsichtlich der Datensicherheit jedoch ein Hemmnis für die Nutzung digitaler Innovationen darstellen. Hier spielt die Kommunikation und Interaktion mit medizinischem Fachpersonal eine entscheidende Rolle, um diese Barrieren abzubauen und dem Bedürfnis nach sozialer Interaktion im Zusammenhang mit digitaler Technologie gerecht zu werden. Die Vermittlung grundlegender Soft Skills sowohl an medizinisches Personal als auch an Patienten, eine transparente Kommunikation über Datenschutzregelungen und den Zweck freiwilliger Datenspenden sowie interdisziplinäre Schulungsprogramme, die technische Anforderungen und auch soziale Aspekte berücksichtigen, sind daher von großer Bedeutung. Unsere Studie betont die Wichtigkeit einer einfühlsamen und individuellen ärztlichen Betreuung, um Ängste und Vorbehalte auf Patientenseite abzubauen und digitale Gesundheitstechnologien effektiv einsetzen zu können. Dieser ganzheitliche Ansatz wird entscheidend dazu beitragen, die Potenziale der Digitalisierung im Gesundheitswesen voll auszuschöpfen. The ever-expanding potential of digital technologies is increasingly influencing healthcare, with a focus on connecting various stakeholders, including patients, healthcare providers, developers, and researchers. To fully realize this potential, it is crucial to nurture and enhance the digital skills of patients, particularly considering demographic changes. Understanding and embracing digital innovations in healthcare are fundamental issues. This study, conducted as a multi-case study within the context of the “Medical Informatics Hub for Saxony” (MiHUBx), aimed to investigate the essential digital competencies required by patients and medical professionals to effectively use digital health technologies. The study also identified influencing factors on these digital competencies, contributing to a strategic approach for developing the necessary digital skills. Our findings reveal that digitization is becoming increasingly integrated into patients’ daily lives but concerns about data security continue to impede the adoption of digital innovations. Effective communication and interaction with medical professionals can play a pivotal role in overcoming these barriers and addressing the desire for social interaction within the realm of digital technology. Therefore, the provision of fundamental soft skills to healthcare professionals and patients, transparent communication regarding data privacy regulations and the purpose of voluntary data contributions, and interdisciplinary training programs that consider technical requirements and social aspects equally are of paramount importance. This study underscores the significance of providing sensitive and individualized support to alleviate fears and reservations, ultimately enabling patients to harness digital health technologies effectively.
  • Zeitschriftenartikel
    The Clinical Data Intelligence Project
    (Informatik-Spektrum: Vol. 39, No. 4, 2016) Sonntag, Daniel; Tresp, Volker; Zillner, Sonja; Cavallaro, Alexander; Hammon, Matthias; Reis, André; Fasching, Peter A.; Sedlmayr, Martin; Ganslandt, Thomas; Prokosch, Hans-Ulrich; Budde, Klemens; Schmidt, Danilo; Hinrichs, Carl; Wittenberg, Thomas; Daumke, Philipp; Oppelt, Patricia G.
    This article is about a new project that combines clinical data intelligence and smart data. It provides an introduction to the “Klinische Datenintelligenz” (KDI) project which is founded by the Federal Ministry for Economic Affairs and Energy (BMWi); we transfer research and development results (R&D) of the analysis of data which are generated in the clinical routine in specific medical domain. We present the project structure and goals, how patient care should be improved, and the joint efforts of data and knowledge engineering, information extraction (from textual and other unstructured data), statistical machine learning, decision support, and their integration into special use cases moving towards individualised medicine. In particular, we describe some details of our medical use cases and cooperation with two major German university hospitals.