@article{3106,
  author = {Samia Nouredine, Abida Toumi, Baarir Zineeddine},
  title = {A New Approach Based Symbiotic Organism Search using Data Mining for Medical Decision},
  journal = {Journal of Digital Information Management},
  year = {2020},
  volume = {18},
  number = {5},
  doi = {https://doi.org/10.6025/jdim/2020/18/5-6/195-209},
  url = {http://dline.info/fpaper/jdim/v18i5_6/jdimv18i5.6_4.pdf},
  abstract = {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. },
}