Pharmaceutical Data Search by Decision Trees

Authors

  • Djamila Benhaddouche Faculty of Mathematics and Computer Science University Of Science and Technology of Oran Mohamed Boudiaf Usto-MB, Oran, Algeria

DOI:

https://doi.org/10.24203/ijcit.v10i1.51

Keywords:

data mining, supervised learning, decision tree, segmentation, fragmentation

Abstract

The number of information concerning the drugs that any professional of health must control in practice and the transformations which they undergo, make the regulation or the administration of drugs difficult for a pregnant woman. Techniques of excavation of data were developed to lead a model of classification of data according to precise criteria. One of   the most used of is the technique of the decision trees, a method making it possible to predict the membership of an individual to a class according to his characteristics; it is based primarily on the relevant attributes of the data base of the field to which it is applied. In our case classification of managed drugs or not with the pregnant woman will be done according to quarters of the pregnancy. The results of this technique will help the professionals of health to take a decision, to make a good regulation, to decrease the accidents related to the catch of inadequate drugs at the period of pregnancy with less risks for the child.

References

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Published

2021-01-31

How to Cite

Pharmaceutical Data Search by Decision Trees. (2021). International Journal of Computer and Information Technology(2279-0764), 10(1). https://doi.org/10.24203/ijcit.v10i1.51

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