Machine learning models for autoverification of medical laboratory test results

Understanding the job of biochemistry specialists while accepting and checking blood test results during in a day where they spend a lot of time, we decided to develop a learning system that can help them. In our experiment we used machine learning models, LibSVM and ANN for classifying the data sets. Because our experiment was started with Artificial Neural Networks (ANN) datasets were obtained from the prior experiment and that approach was tested in a view of Support Vector Machines. We used Replace Missing Values filter for cleaning up the data instances of null values, and correlation of attributes was done with Correlation Attribute Evaluator of WEKA software.