THE IMPORTANCE OF NORMALIZATION METHODS FOR MINING MEDICAL DATA
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2015, Vol 14, Issue 8
Abstract
Over the past decades, the field of medical informatics has been growing rapidly and has drawn the attention of many researchers. The digitization of different medical information, including medical history records, research papers, medical images, laboratory analysis and reports, has generated large amounts of data that need to be handled. As the rate of data acquisition is greater than the rate of data interpretation, new computational technologies are needed in order to manage the resulted repositories of medical data and to extract relevant knowledge from them. Such methods are provided by data mining techniques, which are used for discovering meaningful patterns and trends within the data and help improving various aspects of health informatics. In order to apply data mining techniques, the data needs to be cleansed and transformed, normalization being one of the most important pre-processing methods that accomplish this purpose.This paper aims to present the impact of applying different data normalization methods, on the performance obtained with the K-Nearest Neighbour algorithm on medical data sets.
Authors and Affiliations
Gheorghe Mihaela, Petre Stefania Ruxandra
How Agile Development and Its Tools Support Digital Transformation
Digital transformation is the enabler for new reform of businesses, socialites and governments. It is also the platform to the 2030 Vision in Saudi Arabia and in many other countries. Agile Manifesto succeeded to manage...
An Adaptable Security Framework for Wireless Sensor Networks
The design of secure and survivable nodes is one of the most vital issues in designing energy-efficient protocols for wireless sensor network where the energy, memory and computational power of sensor nodes are limited...
Image Processing: Capturing Student Attendance Data
Role of the student attendance record is very important in the primary, secondary, and tertiary education. The purpose of this record is monitoring student activity in the teaching and learning process and rega...
Enhanced LTrP For Image Retrieval
Local Tetra Pattern (LTrP) is an image retrieval and indexing algorithm for content based image retrieval (CBIR) which made a significant improvement in the precision and recall rates of the retrieved images. Enhanced LT...
Development of Personalized Learning Environment (PLE) for Malaysian School Environment Based on ADDIE Model
Personalized Learning Environment (PLE) is a new concept in designing and developing an online learning. PLE is more focused on individual learning rather than the instructor, facilities, resources and tools. PLE has als...