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Sökning: WFRF:(Weske Mathias)

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  • Kampik, Timotheus, 1989-, et al. (författare)
  • Event log generation : an industry perspective
  • 2022
  • Ingår i: Enterprise, business-process and information systems modeling. - Cham : Springer. - 9783031074752 - 9783031074745 ; , s. 123-136
  • Konferensbidrag (refereegranskat)abstract
    • This paper presents the results of an industry expert survey about event log generation in process mining. It takes academic assumptions as a starting point and elicits practitioner’s assessments of statements about process execution, process scoping, process discovery, and process analysis. The results of the survey shed some light on challenges and perspectives around event log generation, as well as on the relationship between process models and process execution, and derive challenges for event log generation from it. The responses indicate that particularly relevant challenges exist around data integration and quality, and that process mining can benefit from a systematic integration with more traditional and wide-spread business intelligence approaches.
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  • Munoz-Gama, Jorge, et al. (författare)
  • Process mining for healthcare : Characteristics and challenges
  • 2022
  • Ingår i: Journal of Biomedical Informatics. - : Elsevier BV. - 1532-0464 .- 1532-0480. ; 127
  • Tidskriftsartikel (refereegranskat)abstract
    • Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.
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