Agile Workflow Technology and Case-Based Change Reuse for Long-Term Processes

2008 ◽  
Vol 4 (1) ◽  
pp. 80-98 ◽  
Author(s):  
Mirjam Minor ◽  
Alexander Tartakovski ◽  
Daniel Schmalen
Keyword(s):  
Workflow Technology ◽  
Case Based

Agile Workflow Technology for Long-Term Processes

2010 ◽  
pp. 279-298
Author(s):  
Mirjam Minor ◽  
Alexander Tartakovski ◽  
Daniel Schmalen ◽  
Ralph Bergmann
Keyword(s):  
Business Processes ◽  
Case Based Reasoning ◽  
The Novel ◽  
Workflow Technology ◽  
Novel Approach ◽  
New Concepts ◽  
New Process ◽  
Practical Impact ◽  
Case Based

The increasing dynamics of today’s work impacts the business processes. Agile workflow technology is a means for the automation of adaptable processes. However, the modification of workflows is a difficult task that is performed by human experts. This chapter discusses the novel approach of agile workflow technology for dynamic, long-term scenarios and on change reuse. First, it introduces new concepts for a workflow modelling language and enactment service, which enable an interlocked modelling and execution of workflows by means of a sophisticated suspension mechanism. Second, it provides new process-oriented methods of case-based reasoning in order to support the reuse of change experience. The results from an experimental evaluation in a real-world scenario highlight the usefulness and the practical impact of this work.

Individual Prognosis of Diabetes Long-term Risks: A CBR Approach

2001 ◽  
Vol 40 (01) ◽  
pp. 46-51 ◽  
Author(s):  
A. Palaudàries ◽  
E. Plaza ◽  
E. Armengol
Keyword(s):  
Artificial Intelligence ◽  
Diabetic Complication ◽  
Diabetic Patients ◽  
Case Based Reasoning ◽  
Artificial Intelligence Technique ◽  
Past Experiences ◽  
Risk Pattern ◽  
Case Based ◽  
Intelligence Technique

AbstractWe present DIRAS, an application to support physicians in determining the risk of complications for individual diabetic patients. The risk pattern of each diabetic patient is obtained using a Case-based Reasoning method called LID. Case-based Reasoning is an Artificial Intelligence technique based on solving new situations according to past experiences. For each patient, the LID method determines the risk of each diabetic complication according to the risk of already diagnosed patients. In addition, LID builds a description that can be viewed as an explanation of the obtained risk.

scholarly journals 16-61: CIEDs-related endocarditis incidence among a single electrophysiology center: results from a long term prospective case-based study

EP Europace ◽  
2016 ◽  
Vol 18 (suppl_1) ◽  
pp. i16-i16
Author(s):  
Francesco De Sensi ◽  
Alberto Cresti ◽  
Luigi Addonisio ◽  
Marco Breschi ◽  
Gennaro Miracapillo
Keyword(s):  
Case Based

scholarly journals Inductive Learning: Does Interleaving Exemplars Affect Long-Term Retention?

2013 ◽  
Author(s):  
Norehan Zulkiply ◽  
Jennifer S Burt
Keyword(s):  
Inductive Learning ◽  
Study Phase ◽  
Case Based Reasoning ◽  
Short Term ◽  
Actual Performance ◽  
Term Retention ◽  
Mixed Factorial Design ◽  
Long Term Retention ◽  
Case Based

Purpose – The present study investigated whether or not the benefits of interleaving of exemplars from several categories vary with retention interval in inductive learning.   Methodology – Two experiments were conducted using paintings (Experiment 1) and textual materials (Experiment 2), and the experiments used a mixed factorial design. Forty students participated in each experiment for course credit. In each experiment, participants studied a series of exemplars from several categories which were presented massed and interleaved, and later their induction was tested either shortly after the study phase (short-term retention) or after a week’s delay (long- term retention).   Findings – Consistent with findings from previous studies, the interleaving effect was found in the short-term retention condition, and crucially, the present study provided the initial evidence that interleaving of exemplars also affected long-term retention. Interestingly, massing was judged to be more effective than spacing (interleaving) in most groups, even when actual performance showed the opposite.   Significance – The present study shows that interleaved exemplars have considerable potential in improving inductive learning in the long term. For example, induction is used in case-based reasoning which requires one to start with learning from specifi c cases, and then form generalizations of these cases by identifying the commonalities between them. In order to enhance long-term retention, educators may want to consider using interleaved presentation rather than massed presentation in teaching examples or cases from a particular category or concept.

scholarly journals A case-based approach to UTI imaging – making sense of the guidelines

2015 ◽  
Vol 19 (2) ◽  
Author(s):  
Tracy Kilborn ◽  
Halvani Moodley ◽  
Anita Brink ◽  
Peter Nourse
Keyword(s):  
South African ◽  
Renal Damage ◽  
Vesicoureteric Reflux ◽  
Evidence Based ◽  
Making Sense ◽  
Tract Infections ◽  
African Setting ◽  
Case Based ◽  
The Ideal

Urinary tract infections (UTIs) are common amongst children and invariably result in imaging tests to look for correctable causes that may predispose the child to infection. The objective of imaging is to identify those children at risk of long-term renal damage. The ideal imaging algorithm is extensively debated in the literature owing to the lack of evidence-based data, evolving theories on the pathophysiology of UTI and vesicoureteric reflux (VUR). The present article provides a case-based approach to the imaging of UTIs and proposes guidelines relevant to the South African setting.

An intelligent case-based knowledge management system for quality improvement in nursing homes

2018 ◽  
Vol 48 (1) ◽  
pp. 103-121 ◽  
Author(s):  
King Lun Tommy Choy ◽  
Kai Yuet Paul Siu ◽  
To Sum George Ho ◽  
C.H. Wu ◽  
Hoi Yan Lam ◽  
...  
Keyword(s):  
Service Quality ◽  
Training Program ◽  
Nursing Staff ◽  
Service Providers ◽  
Term Care ◽  
Content Type ◽  
Knowledge Based ◽  
Case Based

Purpose This paper aims to maintain the high service quality of the long-term care service providers by establishing a knowledge-based system so as to enhance the service quality of nursing homes and the performance of its nursing staff continually. Design/methodology/approach An intelligent case-based knowledge management system (ICKMS) is developed with the integration of two artificial intelligence techniques, i.e. fuzzy logic and case-based reasoning (CBR). In the system, fuzzy logic is adopted to assess the performance through the analysis of the long-term care services provided, nurse performance and elderly satisfaction, whereas CBR is used to formulate a customized re-training program for quality improvement. A case study is conducted to validate the feasibility of the proposed system. Findings The empirical findings indicate that the ICKMS helps in identification of those nursing staff who cannot meet the essential service standard. Through the customized re-training program, the performance of the nursing staff can be greatly enhanced, whereas the medical errors and complaints can be considerably reduced. Furthermore, the proposed methodology provides a cost-saving approach in the administrative work. Practical implications The findings and results of the study facilitate decision-making using the ICKMS for the long-term service providers to improve their performance and service quality by providing a customized re-training program to the nursing staff. Originality/value This study contributes to establishing a knowledge-based system for the long-term service providers for maintaining the high service quality in the health-care industry.

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