International Journal of Academic Information Systems Research (IJAISR)   Year: 2020 | Volume: 4 | Issue: 11 | Page No.: 1-6 Antibiotic Susceptibility Prediction Using JNN Ahmed Jabara Abu Oriban, Shaima Naji Abdel-Al, Nourhan Abdel Moneim Fouda, Samy S. Abu-Naser Abstract: In this research, an Artificial Neural Network (ANN) model was developed and validated to predict efficiency of antibiotics in treating various bacteria types. Attributes that were taken in account are: organism name, specimen type, and antibiotic name as input and susceptibility as an output. A model based on one input layer, one hidden layer, and one output layer concept topology was developed and trained using a data from Queensland government's website. The evaluation shows that the proposed ANN model using JNN tool is capable of correctly predicting the susceptibility of organisms to the antibiotics with 94.17% accuracy.