Process model comparison based on cophenetic distance

The automated comparison of process models has received increasing attention in the last decade, due to the growing existence of process models and repositories, and the consequent need to assess similarities between the underlying processes. Current techniques for process model comparison are either structural (based on graph edit distances), or behavioural (through activity profiles or the analysis of the execution semantics). Accordingly, there is a gap between the quality of the information provided by these two families, i.e., structural techniques may be fast but inaccurate, whilst behavioural are accurate but complex. In this paper we present a novel technique, that is based on a well-known technique to compare labeled trees through the notion of Cophenetic distance. The technique lays between the two families of methods for comparing a process model: it has an structural nature, but can provide accurate information on the differences/similarities of two process models. The experimental evaluation on various benchmarks sets are reported, that position the proposed technique as a valuable tool for process model comparison.Peer ReviewedPostprint (author's final draft

Merging business process models

This paper addresses the following problem: given two business process models, create a process model that is the union of the process models given as input. In other words, the behavior of the produced process model should encompass that of the input models. The paper describes an algorithm that produces a single configurable process model from a pair of process models. The algorithm works by extracting the common parts of the input process models, creating a single copy of them, and appending the differences as branches of configurable connectors. This way, the merged process model is kept as small as possible, while still capturing all the behavior of the input models. Moreover, analysts are able to trace back which model(s) a given element in the merged model originates from. The algorithm has been prototyped and tested against process models taken from several application domains

Pharmacotherapy in paediatric epilepsy: from trial and error to rational drug and dose selection – a long way to go

Whereas ongoing efforts in epilepsy research focus on the underlying disease processes, the lack of a physiologically-based rationale for drug and dose selection contributes to inadequate treatment response in children. In fact, limited information on the interindividual variation in pharmacokinetics and pharmacodynamics of anti-epileptic drugs (AEDs) in children drive prescription practice, which relies primarily on dose regimens according to a mg/kg basis. Such practice has evolved despite advancements in paediatric pharmacology showing that growth and maturation processes do not correlate linearly with changes in body size. Areas covered: In this review we aim to provide 1) a comprehensive overview of the sources of variability in the response to AEDs, 2) insight into novel methodologies to characterise such variation and 3) recommendations for treatment personalisation. Expert Opinion: The use of pharmacokinetic-pharmacodynamic principles in clinical practice is hindered by the lack of biomarkers and by practical constraints in the evaluation of polytherapy. The identification of biomarkers and their validation as tools for drug development and therapeutics will require some time. Meanwhile, one should not miss the opportunity to integrate the available pharmacokinetic data with modelling and simulation concepts to prevent further delays in the development of personalised treatments for paediatric patients

Similarity of business process models : metrics and evaluation

It is common for large and complex organizations to maintain repositories of business process models in order to document and to continuously improve their operations. Given such a repository, this paper deals with the problem of retrieving those process models in the repository that most closely resemble a given process model or fragment thereof. The paper presents three similarity metrics that can be used to answer such queries: (i) label matching similarity that compares the labels attached to process model elements; (ii) structural similarity that compares element labels as well as the topology of process models; and (iii) behavioral similarity that compares element labels as well as causal relations captured in the process model. These similarity metrics are experimentally evaluated in terms of precision and recall, and in terms of correlation of the metrics with respect to human judgement. The experimental results show that all three metrics yield comparable results, with structural similarity slightly outperforming the other two metrics. Also, all three metrics outperform traditional search engines when it comes to searching through a repository for similar business process models

Effects of caffeine intake prior to stress cardiac magnetic resonance perfusion imaging on regadenoson- versus adenosine-induced hyperemia as measured by T1 mapping

The antagonistic effects of caffeine on adenosine receptors are a possible cause of false-negative stress perfusion imaging. The purpose of this study was to determine the effects of coffee intake <4 h prior to stress perfusion cardiac magnetic resonance imaging (CMR) in regadenoson- versus adenosine-induced hyperemia as measured with T1-mapping. 98 consecutive patients with suspected coronary artery disease referred for either adenosine or regadenoson perfusion CMR were included in this analysis. Twenty-four patients reported coffee consumption <4 h before CMR (15 patients with adenosine, and 9 patients with regadenoson); 74 patients reported no coffee intake (50 patients with adenosine, and 24 patients with regadenoson). T1 mapping was performed using a modified look-locker inversion recovery sequence. T1 reactivity was determined by subtracting T1(rest) from T1(stress). T1(rest), T1(stress), and T1 reactivity in patients referred for regadenoson perfusion CMR were not significantly different when comparing patients with <4 h coffee intake and patients who reported no coffee intake (976 +/- 4 ms, 1019 +/- 48 ms, and 4.4 +/- 3.2% vs 971 +/- 33 ms, 1023 +/- 43 ms, and 5.4 +/- 2.4%) (p = 0.70, 0.79, and 0.40), and similar to values in patients without coffee intake undergoing adenosine CMR. In patients with <4 h coffee intake, T1(stress), and T1 reactivity were significantly lower for adenosine (898 +/- 51 ms, and -7.8 +/- 5.0%) compared to regadenoson perfusion CMR (p <0.001). Coffee intake <4 h prior to regadenoson perfusion CMR has no effect on stress-induced hyperemia as measured with T1 mapping

Measuring similarity between business process models. In:

Abstract. Quality aspects become increasingly important when business process modeling is used in a large-scale enterprise setting. In order to facilitate a storage without redundancy and an efficient retrieval of relevant process models in model databases it is required to develop a theoretical understanding of how a degree of behavioral similarity can be defined. In this paper we address this challenge in a novel way. We use causal footprints as an abstract representation of the behavior captured by a process model, since they allow us to compare models defined in both formal modeling languages like Petri nets and informal ones like EPCs. Based on the causal footprint derived from two models we calculate their similarity based on the established vector space model from information retrieval. We validate this concept with an experiment using the SAP Reference Model and an implementation in the ProM framework

Accurate late gadolinium enhancement prediction by early T1-based quantitative synthetic mapping

OBJECTIVES: Early synthetic gadolinium enhancement (ESGE) imaging from post-contrast T1 mapping after adenosine stress-perfusion cardiac magnetic resonance (CMR) was compared to conventional late gadolinium enhancement (LGE) imaging for assessing myocardial scar. METHODS: Two hundred fourteen consecutive patients suspected of myocardial ischaemia were referred for stress-perfusion CMR. Myocardial infarct volume was quantified on a per-subsegment basis in both synthetic (2-3 min post-gadolinium) and conventional (9 min post-gadolinium) images by two independent observers. Sensitivity, specificity, PPV and NPV were calculated on a per-patient and per-subsegment basis. RESULTS: Both techniques detected 39 gadolinium enhancement areas in 23 patients. The median amount of scar was 2.0 (1.0-3.1) g in ESGE imaging and 2.2 (1.1-3.1) g in LGE imaging (p=0.39). Excellent correlation (r=0.997) and agreement (mean absolute difference: -0.028±0.289 ml) were found between ESGE and LGE images. Sensitivity, specificity, PPV and NPV of ESGE imaging were 96 (78.9-99.9), 99 (97.1-100.0)%, 96 (76.5-99.4) and 99.5 (96.6-99.9) in patient-based and 99 (94.5-100.0), 100 (99.9-100.0)%, 97.0 (91.3-99.0) and 100.0 (99.8-100.0) in subsegment-based analysis. CONCLUSION: ESGE based on post-contrast T1 mapping after adenosine stress-perfusion CMR imaging shows excellent agreement with conventional LGE imaging for assessing myocardial scar, and can substantially shorten clinical acquisition time. KEY POINTS: • Synthetic gadolinium enhancement images can be used for detection of myocardial scar. • Early synthetic gadolinium enhancement images can substantially shorten clinical acquisition time. • ESGE has high diagnostic accuracy as compared to conventional late gadolinium enhancement. • Quantification of myocardial scar with ESGE closely correlates with conventional LGE. • ESGE after stress perfusion CMR avoids need for additional gadolinium administration