Accessing complex patient data from Arden Syntax Medical Logic Modules - Kraus, Stefan; Enders, Martin; Prokosch, Hans-Ulrich; Castellanos, Ixchel; Lenz, Richard; Sedlmayr, Martin (Artificial Intelligence in Medicine, 2018)
OBJECTIVE: Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden Syntax Medical Logic Modules must be able to retrieve patient data from the electronic medical record in order to enable automated decision making. For patient data with a simple structure, for instance a list of laboratory results, or, in a broader view, any patient data with a list or table structure, this mapping process is straightforward. Nevertheless, if patient data are of a complex nested structure the mapping process may become tedious. Two clinical requirements - to process complex microbiology data and to decrease the time between a critical laboratory event and its alerting by monitoring Health Level 7 (HL7) communication - have triggered the investigation of approaches for providing complex patient data from electronic medical records inside Arden Syntax Medical Logic Modules. METHODS AND MATERIALS: The data mapping capabilities of current versions of the Arden Syntax standard as well as interfaces and data mapping capabilities of three different Arden Syntax environments have been analyzed. We found and implemented three different approaches to map a test sample of complex microbiology data for 22 patients and measured their execution times and memory usage. Based on one of these approaches, we mapped entire HL7 messages onto congruent Arden Syntax objects. RESULTS: While current versions of Arden Syntax support the mapping of list and table structures, complex data structures are so far unsupported. We identified three different approaches to map complex data from electronic patient records onto Arden Syntax variables; each of these approaches successfully mapped a test sample of complex microbiology data. The first approach was implemented in Arden Syntax itself, the second one inside the interface component of one of the investigated Arden Syntax environments. The third one was based on deserialization of Extended Markup Language (XML) data. Mean execution times of the approaches to map the test sample were 497ms, 382ms, and 84ms. Peak memory usage amounted to 3MB, 3MB, and 6MB. CONCLUSION: The most promising approach by far was to map arbitrary XML structures onto congruent complex data types of Arden Syntax through deserialization. This approach is generic insofar as a data mapper based on this approach can transform any patient data provided in appropriate XML format. Therefore it could help overcome a major obstacle for integrating clinical decision support functions into clinical information systems. Theoretically, the deserialization approach would even allow mapping entire patient records onto Arden Syntax objects in one single step. We recommend extending the Arden Syntax specification with an appropriate XML data format.
EVALuna2:142

Dimensions of digital twin applications - A literature review - Enders, Martin; Hoßbach, Nadja (25th Americas Conference on Information Systems, AMCIS 2019, 2019)
The use of Digital Twins has gained attraction in research and practice in recent years. Digital Twins are virtual representations of physical objects and they can be connected with their physical counterparts. Through this connection, Digital Twins contribute to the convergence of the real and the virtual world. While existing literature reviews focus strongly on the manufacturing industry, this paper analyzes Digital Twin applications across industries. Based on a systematic literature review, this paper examines 87 Digital Twin applications and proposes a classification scheme with six dimensions to describe the applications identified. The concept of Digital Twins is currently still underrepresented in Information Systems research, which opens up further research opportunities.
CRIS-Team Scopus Importer:2019-10-25
Keywords: Digital Twin; Literature Review

Towards a semi-automated approach for systematic literature reviews - Denzler, Tim; Enders, Martin; Akello, Patricia (27th Annual Americas Conference on Information Systems, AMCIS 2021, 2021)
Given the growing output of scientific literature, researchers are faced with a daunting challenge when it comes to performing systematic literature reviews. Hence, the use of Information Systems to achieve operational excellence has gained increasing importance in systematic literature reviews. However, existing solutions to support systematic literature reviews are often restrained to a single aspect of the process or lack interoperability. As such, researchers may not be able to efficiently leverage recent promising advancements in Machine Learning and Text Analytics. Therefore, we developed a flexible and modifiable artifact that aims to support systematic literature review processes from a holistic point of view. We expect our artifact to be a first step towards semi-automation of systematic literature reviews, which will gain relevance in the near future, as the trend of rising scientific literature output is expected to continue. Our development process follows a Design Science Research approach including continuous evaluation.
CRIS-Team WoS Importer:2021-08-20
Keywords: Automation; Design science; Information systems; Literature review; Machine learning; Text analytics