01615nas a2200157   4500008004100000245009100041210006900132260002000201300001200221490000700233520110900240100002101349700001701370700002301387856004701410       2020                        eng d00aA New Approach Based Symbiotic Organism Search using Data Mining for Medical Decision-0 aNew Approach Based Symbiotic Organism Search using Data Mining f  c10/2020,12/2020  a195-2090 v183 a<p><span style="color: rgb(51, 51, 51); font-family: Arial, Helvetica, sans-serif;">In the medical field the decision represents an extremely important asset because the risk must be zero. This is why decision approaches which are based on a predictive vision are a must solution. The decision is generally based on the exploitation of a large volume of medical data. The processing and analysis of mass data is only possible through an extraction of knowledge allowing the medical experts to make the best decision. Thus to meet this need, data mining has become the most promising approach. There are several techniques of datamining, and although they are quite developed the y still remain even less efficient notably the classical meta-heuristics. In this paper, we are exploiting a new meta-heuristic called symbiotic organisms search (SOS) that is based on a biological process. In this paper, we develop the formal model of the SOS based data mining process in the medical field with a comparative study with other metaheuristics to show its performance and credibility of treatment.</span></p>
1 aNouredine, Samia1 aToumi, Abida1 aZineeddine, Baarir  uhttp://www.dline.info/download.php?sn=3104