A NSGA-II APPLICATION WITH DIFFERENT GENE EXPRESSION TECHNOLOGIES INTEGRATION
Published In: 6TH INTERNATIONAL CONFERENCE ON ADVANCES IN BIO-INFORMATICS, BIO-TECHNOLOGY AND ENVIRONMENTAL ENGINEERING
Author(s): DANIEL CASTILLO , IGNACIO ROJAS , JUAN MANUEL GALVEZ , OLGA VALENZUELA
Abstract: Thanks to genetic expression, biomarkers related to much kind of diseases could be obtained. However, depending on the previous experimental constraints, these biomarkers can become too many, especially if they are intended to be used in a classification process. Multi-Objective Genetic Algorithm (MOGA) has been thought of as a suitable solution to get a tradeoff among candidate biomarkers and classification accuracy. In this sense, genetic expression and Non Sorting Genetic Algorithm (NSGA) are combined in order to obtain the minimum number of possible genes that achieve the maximum classification accuracy. Only with a few genes, the classifier is expected to be more computationally efficient and faster than with all the genes, besides not endangering the final accuracy.
- Publication Date: 29-Apr-2018
- DOI: 10.15224/978-1-63248-148-1-05
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FORECASTING POTENTIAL HEALTH THREATS USING MACHINE LEARNING A HARDARE / SOFTWARE APPROACH
Published In: 6TH INTERNATIONAL CONFERENCE ON ADVANCES IN BIO-INFORMATICS, BIO-TECHNOLOGY AND ENVIRONMENTAL ENGINEERING
Author(s): DEVAHARSHA MEESARAPU , NISHANT RAMAKURU , YASH DEO
Abstract: The idea proposes that an amalgamation of hardware input/output with the right software can be used to forecast and potentially avoid future health threats.
- Publication Date: 29-Apr-2018
- DOI: 10.15224/978-1-63248-148-1-06
- Views: 0
- Downloads: 0