A Multi-Level Process Mining Framework for Correlating and Clustering of Biomedical Activities using Event Logs

Naeem, Muhammad Rashid; Naeem, Hamad; Aamir, Muhammad; Ali, Waqar; Abro, Waheed Ahmed

doi:10.14569/ijacsa.2017.080354

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…Notwithstanding, infrequent behavior is essential in terms of compliance perspective, and such behavior might also have alternative explanations, such as anomalous behavior that triggers the need for further investigation. A similar approach was used by Rashid et al [76] to deal with complexity. They set a frequency-based threshold, removed infrequent behavior against it, and relied on visual analysis.…”

Section: ) Noise Filtration Approachesmentioning

confidence: 99%

Complex Process Modeling in Process Mining: A Systematic Review

et al. 2022

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Process mining techniques are used to extract knowledge about the efficiency and compliance of an organization's business processes through process models. Real-life processes are unstructured, and applying process mining to discover such processes often results in complex process models that do not provide actionable insights. Several solutions have been presented to overcome this problem. However, the process mining domain lacks an explicit definition of complexity and its measurement. This vagueness results in ad-hoc solutions that vary according to the approach, modelling construct, and process properties. Additionally, the strength and limitations of the proposed solutions have not been adequately highlighted. Therefore, we conducted a systematic literature review on complexity in process mining over six popular scholarly indexing databases. Based on the review results, an explicit definition of complexity, the main contributing factors and their impact on process mining results were identified. We discovered various process complexity matrices and their application context. The analysis of studies led to the development of a taxonomy consisting of four different approaches for addressing the complexity problem, along with their strengths and limitations. Finally, the open research challenges and potential for future research are discussed.

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Section: ) Noise Filtration Approachesmentioning

confidence: 99%

Complex Process Modeling in Process Mining: A Systematic Review

et al. 2022

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“…The automated approach of process mining offers an alternative to manually creating healthcare process models, which is hard and tedious work due to the vast amount of domain knowledge that is required. Process mining techniques have been applied to different aspects of healthcare processes in the past (Huang et al 2014(Huang et al , 2015Lismont et al 2016;Mans et al 2009;Rashid et al 2017;Rismanchian and Lee 2017;Rojas et al 2016;Rovani et al 2015;Wang et al 2017). However, these applications typically target more standardized processes while using imperative modeling languages as a foundation.…”

Section: Related Workmentioning

confidence: 99%

Enabling Process Management for Loosely Framed Knowledge-intensive Processes

Mertens¹

2020

Lecture Notes in Business Information Processing

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If you don't have a PhD: yes, this statement is accurate. A little sympathy wouldn't hurt, you know.If you're currently doing a PhD: your brain is probably already pregnant. I feel you. Every day it gets a little harder to drag your ailing body out of bed. Dealing with the occasional morning sickness (unrelated to last night's drinking). The prospect of the dreaded third trimester looming (i.e., writing the book and numerous postdoc proposals). Maybe it's not too late to consider a late-term abortion?If you have a PhD: congratulations! You won… Erm… Well what did you win? I guess you can proudly call yourself a doctor. However, don't bother getting up when someone yells out for a doctor on a plane. They will not be as impressed with the highest academic degree as one might expect. Now skip past the rest of this preface section, read this book from cover to cover, and only afterwards return here to read the rest. No cheating! You will be quizzed! Who am I kidding? You're probably not actually going to bother with the rest of this book. Just like if I would be presenting you my newborn, you're going to congratulate me and disappear as soon as you get a whiff of its insides… How about trying to imagine reading this book from cover to cover? It's over 200 pages of scientific and peer-reviewed work. That's a lot, right? Now imaging having to write such a behemoth. Each chapter/paper needs a problem statement, relevant research questions, a methodology to find answers to those questions, a literature review of the state-of-the-art on the subject and, most importantly, a description of actual contributions to that state-of-the-art. Each chapter/section/paragraph/sentence/word carefully written, criticized by peers, rewritten, criticized by peers, rewritten again, criticized by peers, etc. until everyone involved starts to involuntarily cringe at the mere thought of it. But you can't just start writing. A paper is merely a report of research ii that you would've already done by then. The research consists of formulating interesting, relevant and unsolved problems, which you subsequently must tackle head-onfully aware of the fact that it had probably already crossed the minds of other researchers, who had likely discarded the idea because they considered it an insurmountable problem that only fools would waste their time on.And yet again, you cannot just start formulating interesting, relevant and unsolved problems without being an expert on a certain subject. How do you become an expert? Reading, more reading, even more reading and -you've guessed itsome more reading (my favorite pastime!). Luckily, you can stop when you've learned enough buzzwords to fool other researchers into thinking that you know what you're talking about. Fake it till you make it! After all, we're living in the Trump-era… "I know words, I have the best words" Donald J. Trump, 45th president of the United States of America But before you can start reading up on a certain subject, you need to choose a suitable subject.Something that interests you in ...

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“…The automated approach of process mining offers an alternative to manually creating health-care process models, which is hard and tedious work due to the vast amount of domain knowledge that is required. Process mining techniques have been applied to different aspects of health-care processes in the past (Huang et al, 2014;Huang, Dong, Bath, Ji, & Duan, 2015;Lismont et al, 2016;Mans, Schonenberg, Song, Van Der Aalst, & Bakker, 2009;Rashid, Naeem, Aamir, Ali, & Ahmed, 2017;Rismanchian & Lee, 2017;Rojas, Munoz-Gama, Sepúlveda, & Capurro, 2016;Rovani et al, 2015;Wang, Tian, Yu, Qi, & Yang, 2017). However, these applications typically target more standardised processes while using imperative modelling languages as a foundation.…”

Section: Related Researchmentioning

confidence: 99%

Discovering health-care processes using DeciClareMiner

2017

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Flexible, human-centric and knowledge-intensive processes occur in many service industries and are prominent in the health-care sector. Knowledge workers (e.g., doctors or other health-care personnel) are given the flexibility to address each process instance (i.e., episode of care) in the way that they deem most suitable. As a result, the knowledge of these processes is generally of a tacit nature, with many stakeholders lacking a clear view of a process. In this paper, we propose an algorithm called DeciClareMiner that combines process and decision mining to extract a process model and the corresponding knowledge from past executions of these processes. The algorithm was evaluated by applying it to a realistic health-care case and comparing the results to a complete search benchmark. In a relatively short time (10 min), DeciClareMiner was able to produce a DeciClare model that represents 93% of episodes of care with atomic constraints. Compared to the 50 h required to calculate the 100%-episode model via an exhaustive search approach, our result is considered a major improvement.

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A Multi-Level Process Mining Framework for Correlating and Clustering of Biomedical Activities using Event Logs

Cited by 3 publications

References 15 publications

Complex Process Modeling in Process Mining: A Systematic Review

Complex Process Modeling in Process Mining: A Systematic Review

Enabling Process Management for Loosely Framed Knowledge-intensive Processes

Discovering health-care processes using DeciClareMiner

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