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85 Publications visible to you, out of a total of 85
Management of ARDS: From ventilation strategies to intelligent technical support – Connecting the dots
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Julian Kunze, Sebastian Fritsch, Arne Peine, Oliver Maaßen, Gernot Marx, Johannes Bickenbach

Date Published: 1st May 2020

Publication Type: Journal article

Hospital-wide ELectronic medical record evaluated computerised decision support system to improve outcomes of Patients with staphylococcal bloodstream infection (HELP): study protocol for a multicentre stepped-wedge cluster randomised trial
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: Stefan Hagel, Julia Gantner, Cord Spreckelsen, Claudia Fischer, Danny Ammon, Kutaiba Saleh, Lo An Phan-Vogtmann, Andrew Heidel, Susanne Müller, Alexander Helhorn, Henner Kruse, Eric Thomas, Florian Rißner, Silke Haferkamp, Jens Vorwerk, Saskia Deffge, Marc Fabian Juzek-Küpper, Norman Lippmann, Christoph Lübbert, Henning Trawinski, Sebastian Wendt, Thomas Wendt, Andreas Dürschmid, Margarethe Konik, Stefan Moritz, Daniel Tiller, Rainer Röhrig, Jonas Schulte-Coerne, Jonas Fortmann, Stephan Jonas, Oliver Witzke, Peter-Michael Rath, Mathias W Pletz, André Scherag

Date Published: 10th Feb 2020

Publication Type: Journal article

Human Diseases: staphyloenterotoxemia

Agiles Lernzielmanagement mit dem Health Informatics-Learning Objective Navigator (HI-LONa)
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Fragestellung/Zielsetzung: Zentraler Baustein curricularer Entwicklung sind kompetenzorientierte Lernziele [ref:1], wie sie im NKLM dargestellt sind. Webbasierte Datenbanken machen Lernzielkataloge … zugänglich und strukturiert nutzbar. Das Web-Portal LOOOP [ref:2] bietet[zum vollständigen Text gelangen Sie über die oben angegebene URL]

Authors: Ulrike Schemmann, Birgit Schneider, Lo An Phan-Vogtmann, Susanne Müller, Cord Spreckelsen

Date Published: 2020

Publication Type: Misc

Ontological Modelling and Reasoning of Phenotypes
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological … studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term ‘phenotype’ has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimization. In the context of a methodological use case “phenotype pipeline” (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. In this article we present a Core Ontology of Phenotypes (COP) and a software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model and calculate phenotypes. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated based on different phenotypes (including SOFA score, socioeconomic status, body surface area and WHO BMI classification) and several data sets.

Authors: Alexandr Uciteli, Christoph Beger, Toralf Kirsten, Frank A. Meineke, Heinrich Herre

Date Published: 20th Dec 2019

Publication Type: InProceedings

Rückverfolgbarkeit für künstliche Intelligenz: Umsetzung einer Traceability-Strategie bei der modellgetriebenen Entwicklung klinischer Entscheidungsunterstützungssysteme
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Einleitung: Systeme auf Basis von Algorithmen mit \glqqkünstlicher Intelligenz\grqq werden im Gesundheitswesen zunehmend praktisch eingesetzt. Durch die Medizininformatik-Initiative sollen zukünftig … Daten aus Krankenversorgung und Forschung besser zugänglich werden. In diesem Rahmen[zum vollständigen Text gelangen Sie über die oben angegebene URL]

Authors: Lo Phan-Vogtmann an , Henner M. Kruse, Alexander Helhorn, Andrew J. Heidel, Eric Thomas, Kutaiba Saleh, André Scherag, Danny Ammon

Date Published: 8th Sep 2019

Publication Type: InProceedings

Modeling a Graph Data Model for FHIR Resources
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Introduction: (Fast Healthcare Interoperability Resources) is a modern standard for communication and representation of clinical data, where each dataset is defined by a single resource, linked to other … resources [ref:1]. But FHIR\circledR does explicitely not define how to persist these resources[for full text, please go to the a.m. URL]

Authors: Henner M. Kruse, Alexander Helhorn, Lo Phan-Vogtmann an , Eric Thomas, Andrew J. Heidel, Kutaiba Saleh, André Scherag, Danny Ammon

Date Published: 6th Sep 2019

Publication Type: InProceedings

Design and Concept of the SMITH Phenotyping Pipeline.
SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Phenotyping means the determination of clinical relevant phenotypes, e.g. by classification or calculation based on EHR data. Within the German Medical Informatics Initiative, the SMITH consortium is … working on the implementation of a phenotyping pipeline. to extract, structure and normalize information from the EHR data of the hospital information systems of the participating sites; to automatically apply complex algorithms and models and to enrich the data within the research data warehouses of the distributed data integration centers with the computed results. Here we present the overall picture and essential building blocks and workflows of this concept.

Authors: F. A. Meineke, S. Staubert, M. Lobe, A. Uciteli, M. Loffler

Date Published: 3rd Sep 2019

Publication Type: Journal article

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The Health Atlas - Local Data Hub/Leipzig is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

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