Soft Computing, Artificial Intelligence and Applications

Cancer Prognosis Prediction Using Balanced Stratified Sampling J.S.Saleema1, N.Bhagawathi2, S.Monica2, P.Deepa Shenoy2, K.R.Venugopal2 and L.M.Patnaik3 1Christ University, India 2University Visvesvaraya College of Engineering, India 3Indian Institute of Science, India ABSTRACT High accuracy in cancer prediction is important to improve the quality of the treatment and to improve the rate of survivability of patients. As the data volume is increasing rapidly in the healthcare research, the analytical challenge exists in double. The use of effective sampling technique in classification algorithms always yields good prediction accuracy. The SEER public use cancer database provides various prominent class labels for prognosis prediction. The main objective of this paper is to find the effect of sampling techniques in classifying the prognosis variable and propose an ideal sampling method based on the outcome of the experimentation. In the first phase of this work the traditio...

Cancer Prognosis Prediction Using Balanced Stratified Sampling J.S.Saleema1, N.Bhagawathi2, S.Monica2, P.Deepa Shenoy2, K.R.Venugopal2 and L.M.Patnaik3, 1Christ University, India 2University Visvesvaraya College of Engineering, India 3Indian Institute of Science, India ABSTRACT High accuracy in cancer prediction is important to improve the quality of the treatment and to improve the rate of survivability of patients. As the data volume is increasing rapidly in the healthcare research, the analytical challenge exists in double. The use of effective sampling technique in classification algorithms always yields good prediction accuracy. The SEER public use cancer database provides various prominent class labels for prognosis prediction. The main objective of this paper is to find the effect of sampling techniques in classifying the prognosis variable and propose an ideal sampling method based on the outcome of the experimentation. In the first phase of this work the traditional rando...

A Naive Method For Ontology Construction Preeti Kathiria and Sukraat Ahluwalia Nirma University, India ABSTRACT Ontologies are being used to organizeinformation in many domains like artificial intelligence,information science, semantic web, library science. Ontologies of an entity having different information can be merged to create more knowledge of that particular entity. Ontologies today are powering more accurate search and retrieval in websites like Wikipedia etc. As we move towards the future to Web 3.0,also termed as the semantic web, ontologies will play a more important role.Ontologies are represented in various forms like RDF, RDFS, XML, OWL etc. Querying ontologies can yield basic information about an entity. This paper proposes an automated method for ontology creation,using concepts from NLP (Natural Language Processing), Information Retrieval and Machine Learning.Concepts drawn from these domains help in designing more accurate ontologies represented using the XML fo...

<span style="color:#0000ff;"><strong>A BINARY BAT INSPIRED ALGORITHM FOR THE CLASSIFICATION OF BREAST CANCER DATA </strong></span> <p style="text-align:center;"><span style="color:#ff0000;"><strong>Doreswamy and Umme Salma M</strong></span> <span style="color:#ff0000;"><strong>Mangalore University, Mangalagangothri, Mangalore,India, </strong></span></p> <p style="text-align:justify;"><span style="color:#800000;"><strong>ABSTRACT</strong></span></p> <p style="text-align:justify;">Advancement in information and technology has made a major impact on medical science where the researchers come up with new ideas for improving the classification rate of various diseases. Breast cancer is one such disease killing large number of people around the world. Diagnosing the disease at its earliest instance ...