Decision-Making System by Neuronal Networks for Taking into Care Children Suffering from Serious Paludism
Neuronal networks developed since these last thirty years simultaneously at the paradigm of learning. According to this paradigm, machines are not programmed in advance for any given task but learn to carry out this task from examples. By pursuing our analyses in field, we present in this research a contribution in setting up a system to grant benefits of children suffering from serious paludism. Several cases amounting to millions on record each year around the world, with a great vulnerability or children lower than 5 years old. How to prevent these risks of complication and act on time on the basis of diagnosis taken from the patient?
Keywords: learning, neuronal network, serious paludism
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ABOUT THE AUTHORS
Eugene Mbuyi Mukendi
Professor of the University of Kinshasa, Department of Computer Sciences, DR Congo
Alpha Mbuyi Mitongu
The University of Kinshasa, Department of Computer Sciences, DR Congo
Patrick Tshimanga Kapuba
The University of Kinshasa, Department of Computer Sciences, DR Congo
Eugene Mbuyi Mukendi
Professor of the University of Kinshasa, Department of Computer Sciences, DR Congo
Alpha Mbuyi Mitongu
The University of Kinshasa, Department of Computer Sciences, DR Congo
Patrick Tshimanga Kapuba
The University of Kinshasa, Department of Computer Sciences, DR Congo
