Journal of Health & Medical Informatics

Feleke Doyore

Publications

• Research Article
  Application of Data Mining Techniques to Predict Urinary Fistula Surgical Repair Outcome: The Case of Addis Ababa Fistula Hospital, Addis Ababa, Ethiopia
  Author(s): Minale Tefera, Mitike Mola, Getachew Jemaneh and Feleke DoyoreMinale Tefera, Mitike Mola, Getachew Jemaneh and Feleke Doyore
  
  Background: Maternal outcomes are good in most countries of the developed world while the same is not true in many developing countries. The likelihood of the occurrence of incontinence after successful surgical repair makes predicting urinary fistula surgical repair outcome is important for decision making during treatment and follow up. Therefore, this research is aimed to apply data mining techniques to build a model that can assist in predicting surgical outcome of urinary fistula repair based on clinical assessments done just before surgical repair. Methods: The six-step hybrid knowledge discovery process model is used as a framework for the overall activities in the study. 15961 instances that have undergone urinary fistula repair in Addis Ababa Fistula Hospital are used for both predictive association rule extraction and predictive mode.. Read More»
  DOI: 10.4172/2157-7420.1000153

  Abstract PDF