Phenotypes Determined by Cluster Analysis and Their Survival in the Prospective European Scleroderma Trials and Research Cohort of Patients With Systemic Sclerosis

Objective: Systemic sclerosis (SSc) is a heterogeneous connective tissue disease that is typically subdivided into limited cutaneous SSc (lcSSc) and diffuse cutaneous SSc (dcSSc) depending on the extent of skin involvement. This subclassification may not capture the entire variability of clinical phenotypes. The European Scleroderma Trials and Research (EUSTAR) database includes data on a prospective cohort of SSc patients from 122 European referral centers. This study was undertaken to perform a cluster analysis of EUSTAR data to distinguish and characterize homogeneous phenotypes without any a priori assumptions, and to examine survival among the clusters obtained. / Methods: A total of 11,318 patients were registered in the EUSTAR database, and 6,927 were included in the study. Twenty‐four clinical and serologic variables were used for clustering. / Results: Clustering analyses provided a first delineation of 2 clusters showing moderate stability. In an exploratory attempt, we further characterized 6 homogeneous groups that differed with regard to their clinical features, autoantibody profile, and mortality. Some groups resembled usual dcSSc or lcSSc prototypes, but others exhibited unique features, such as a majority of lcSSc patients with a high rate of visceral damage and antitopoisomerase antibodies. Prognosis varied among groups and the presence of organ damage markedly impacted survival regardless of cutaneous involvement. / Conclusion: Our findings suggest that restricting subsets of SSc patients to only those based on cutaneous involvement may not capture the complete heterogeneity of the disease. Organ damage and antibody profile should be taken into consideration when individuating homogeneous groups of patients with a distinct prognosis

A Case Study in Workflow Scheduling Driven by Log Data

This paper shows through a case study the potential for optimizing resource allocation in business process execution. While most resource allocation mechanisms focus on assigning resources to the tasks that they are authorized to perform, we assign resources to the tasks that they can provably perform most efficiently, by mining the execution logs. This gives rise to the minimization of the cost of the process execution. We present various cost measures and how hybrid algorithms can balance their conflicting goals. Our case study indicates significant potential for further research into optimal resource allocation mechanisms.</p

E-government services:comparing real and expected user behavior

\u3cp\u3eE-government web services are becoming increasingly popular among citizens of various countries. Usually, to receive a service, the user has to perform a sequence of steps. This sequence of steps forms a service rendering process. Using process mining techniques this process can be discovered from the information system’s event logs. A discovered process model of a real user behavior can assist in the analysis of service usability. Thus, for popular and well-designed services this process model will coincide with a reference process model of the expected user behavior. While for other services the observed real behavior and the modeled expected behavior can differ significantly. The main aim of this work is to suggest an approach for the comparison of process models and evaluate its applicability when applied to real-life e-government services.\u3c/p\u3

Preference-based resource and task allocation in business process automation

Preference plays an important role in organisational and human decision making as it may be a manifestation of proven practices or of individual working styles. The significance of the notion of preference has been recognised in a number of different disciplines. Unfortunately its potential does not seem to have been fully unlocked in the field of Business Process Automation (BPA), even though resource and task allocations play a pivotal role in process performance and these allocations could be guided by explicit formulations of preferences. In this paper, we examine the state of the art with respect to preference in the field of BPA and use this as the basis for a conceptual model capturing recognised manifestations of preference in the literature. We investigate how preferences may exhibit themselves in process automation through the notion of well-established (workflow) resource patterns. We then show that manifestations of preference may occur in real-life process event logs and how these can be extracted through the application of machine learning techniques. The findings from this research contribute towards establishing a rich understanding of preferences in the context of business processes, ways of specifying and deriving these preferences, and their more explicit incorporation in work allocation mechanisms, which can lead to a step change for realising better process performance and more effective work collaboration in today’s organisations

A Method to Enable Ability-Based Human Resource Allocation in Business Process Management Systems

Part 1: Business Process ModelingInternational audienceBusiness process management systems are used to orchestrate the activities in an organization. These information systems allocate resources to perform activities based on information that describes those resources and activities. It is widely recognized that resource allocation can be enhanced by considering resource characteristics during selection. However, little guidance is available that shows how such characteristics should be specified. Human ability is one such characteristic, with the advantage that it is well-defined in the Fleishman Taxonomy of Human Abilities. This paper presents a method that leverages the Fleishman taxonomy to specify activities and human resources. Those specifications are then used to allocate resources to activities during process run-time. We show how ability-based resource allocation can be implemented in a business process management system and evaluate the method in a real-world scenario