Due to the limitation of the methodologies of traditional data mining to satisfy business expectations, the shift from mining data-centered hidden patterns to domain-driven actionable knowledge discovery has become a significant direction of KDD research [22]. Traditional data mining algorithms and tools face major obstacles and challenges to solve real-life business problems and issues as they fail to provide actions that can be taken by people in business based on generated rules [22]. A small set of rules are generated by standard classification algorithms to form a classifier, but these classification algorithms use domain independent biases and heuristics [2]. This research aimed to propose a new approach to find actionable rules from sets of discovered rules. It focused on how a combination of traditional classification data mining and domain-driven data mining approach could be applied in solving real-life problems related to the field of traffic accidents in UAE. Real-life data were collected and pre-processed using the user’s existing knowledge and needs. Classification using Rules Induction was applied on the domain-driven dataset. The discovered rules from this technique were then summarized, combined, and analyzed. The final set of actionable rules from Classification technique for each class was then generated using a proposed interestingness method. To support such a process, the domain driven in-depth pattern discovery (DDID-PK) framework was followed [9]. Based on experimental results, the extracted domain-driven rules were more interesting and actionable than those produced by the traditional classification technique of data mining. In addition, the integration of data-centered classification technique of data mining to domain-driven approach of data mining and actionable knowledge discovery could help the Dubai police authority to reduce traffic accident severity by formulating new policies and traffic rules based on the domain-driven knowledge extracted from some hidden patterns from real data.
Background: Stress urinary incontinence is one of the most frequently observed health problems among multipara women and has a significant impact on physical health, psychological wellbeing and social functioning. This study aimed to evaluate the effect of educational program on multipara women's knowledge, practice and attitude regarding stress urinary incontinence. Design: Quasi experimental time series design (Pre and posttest) was used. Setting: This study was conducted at komhamada general hospital. Sample: A Purposive sample was used and was about 70 cases. Tools: Tool 1: Interviewing questionnaire. Tool II: Multipara women's self-care practices regarding stress urinary incontinence. Tool III: Likert attitude scale. Tool IV: Incontinence severity index. Tool V: Follow up card for multipara women with stress urinary incontinence. Results: The study results showed a highly statistically significant improvement regarding their knowledge, practice and attitude post intervention compared to pre intervention regarding stress urinary incontinence P<0.001. There was highly statistically significant relation between total knowledge, total attitude & total self-care practice of multipara women with stress urinary incontinence P<0.05. Conclusion: Implementing educational program for multipara women with stress urinary incontinence had highly statistically significant positive effect on multipara women's knowledge, attitude and self-care practice. Recommendation: Increase health awareness of multipara women with stress urinary incontinence about the importance of self -care practices.
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