Impact of selected pre-processing techniques on prediction of risk of early readmission for diabetic patients in India

Duggal, Reena; Khatri, Sunil; Shukla, Suren; Chandra, Sarika; Shukla, Balvinder
December 2016
International Journal of Diabetes in Developing Countries;Dec2016, Vol. 36 Issue 4, p469
Academic Journal
The article focuses on data pre-processing methods to improve readmission prediction outcomes for diabetic patients in India. It discusses data mining or extraction through electronic medical record (EMR) system. Topics include data selection with criteria such as length of stay (LOS), inpatient hospital admission and defining class labels; and predictive modelling using logistic regression, Naive Bayes and decision tree.


Related Articles

  • INTRUSION DETECTION USING BAYESIAN CLASSIFIER FOR ARBITRARILY LONG SYSTEM CALL SEQUENCES. Assem, Nasser; Rachidi, Tajjeeddine; Graini, Mohamed Taha El // IADIS International Journal on Computer Science & Information Sy;2014, Vol. 9 Issue 1, p71 

    In this paper, we present a sequence classifier for detecting host intrusions from long process system call sequences. The proposed classifier (called SC2.2) is a naïve Bayes classifier that builds class conditional probabilities from Markov modeling of system call sequences. We describe the...

  • Data Leakage Detection Using Dynamic Data Structure and Classification Techniques. Guevara Maldonado, César Byron // Inge-Cuc;Jun2015, Vol. 11 Issue 1, p79 

    Data leakage is a permanent problem in public and private institutions around the world; particularly, identifying the information leakage efficiently. In order to solve this problem, this paper poses an adaptable data structure based on human behavior using all the activities executed within...

  • A new computational strategy for predicting essential genes. Jian Cheng; Wenwu Wu; Yinwen Zhang; Xiangchen Li; Xiaoqian Jiang; Gehong Wei; Shiheng Tao // BMC Genomics;2013, Vol. 14 Issue 1, p1 

    Background Determination of the minimum gene set for cellular life is one of the central goals in biology. Genome-wide essential gene identification has progressed rapidly in certain bacterial species; however, it remains difficult to achieve in most eukaryotic species. Several computational...

  • Alleviating Naive Bayes Attribute Independence Assumption by Attribute Weighting. Zaidi, Nayyar A.; Cerquides, Jesüs; Carman, Mark J.; Webb, Geoffrey I. // Journal of Machine Learning Research;Jul2013, Vol. 14 Issue 7, p1947 

    Despite the simplicity of the Naive Bayes classifier, it has continued to perform well against more sophisticated newcomers and has remained, therefore, of great interest to the machine learning community. Of numerous approaches to refining the naive Bayes classifier, attribute weighting has...

  • Bank Direct Marketing Analysis of Data Mining Techniques. Elsalamony, Hany A. // International Journal of Computer Applications;Jan2014, Vol. 85, p12 

    All bank marketing campaigns are dependent on customers' huge electronic data. The size of these data sources is impossible for a human analyst to come up with interesting information that will help in the decision-making process. Data mining models are completely helping in the performance of...

  • Comparisons of Parametric and Non-Parametric Classification Rules for E-Nose and E-Tongue. Mahat, Nor Idayu; Zakaria, Ammar; Md Shakaff, Ali Yeon // AIP Conference Proceedings;2015, Vol. 1691, p1 

    This paper evaluates the performance of parametric and non-parametric classification rules in sensor technology. The growing of sensor technologies, e-nose and e-tongue, has urged engineers to equip themselves with the utmost recent and advanced statistical approaches. As data collected from...

  • Decision Factors on Effective Liver Patient Data Prediction. Hoon Jin; Seoungcheon Kim; Jinhong Kim // International Journal of Bio-Science & Bio-Technology;2014, Vol. 6 Issue 4, p167 

    Various types of stress and irregular eating habits, as well as inhalation of alcohol and ongoing toxic gas, ingestion of contaminated food, excessive consumption of pickled food and drug intake, enables liver disease patients to grow up year by year. To this end, variety of data mining...

  • PARM: A NOVEL POSITIVE ASSOCIATION RULE MINING ALGORITHM FOR DISCOVERING MALEVOLENT APPLICATIONS IN WINDOWS OPERATING SYSTEMS. R, Chandrasekar; Deepa, N. // International Journal of Engineering & Technology (0975-4024);Jun/Jul2013, Vol. 5 Issue 3, p2461 

    The most important vulnerability to the current World Wide Web is the malevolent applications. Generally, these applications are used for interrupting the normal functioning of a system and accessing unprivileged and confidential data and other wicked activities. Malevolent applications were...

  • Predicting Students' Performance using Modified ID3 Algorithm. L., Ramanathan; Dhanda, Saksham; D., Suresh Kumar // International Journal of Engineering & Technology (0975-4024);Jun/Jul2013, Vol. 5 Issue 3, p2491 

    The ability to predict performance of students is very crucial in our present education system. We can use data mining concepts for this purpose. ID3 algorithm is one of the famous algorithms present today to generate decision trees. But this algorithm has a shortcoming that it is inclined to...

  • Performance Comparison between Naïve Bayes, Decision Tree and k-Nearest Neighbor in Searching Alternative Design in an Energy Simulation Tool. Ashari, Ahmad; Paryudi, Iman; Tjoa, A. Min // International Journal of Advanced Computer Science & Application;Nov2013, Vol. 4 Issue 11, p33 

    Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. Commonly it has a feature providing alternative designs that are better than the user's design. In this paper, we propose a novel method in searching alternative design that is by using...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics