Abstract—Artificial Intelligence has significantly gained
grounds in our daily livelihood in this age of information and
technology. As with any field of study, evolution takes place in
terms of breakthrough or developmental research leading to
advancement and friendly usability of that specific technology.
Problems from different areas have been successfully solved
using Artificial Intelligence algorithms. In order to use AI
algorithms in solving Personalized Medicine problems such as;
disease detection or prediction, accurate disease diagnosis, and
treatment optimization, the choice of the algorithm influenced
by its ability and applicability matters. This paper reviews the
application and ability of artificial neural network (ANN),
support vector machines (SVM), Naïve Bayes, and fuzzy logic in
solving personalized medicine problems, and shows that the
obtained results meet expectations. Also, the achievement from
the previous studies encourages developers and researchers to
use these algorithms in solving Medical and Personalized
Medicine problems.
Index Terms—Personalized medicine, artificial neural
networks, support vector machines, Naive Bayesian.
Jamilu Awwalu is with the Faculty of Computer Science and IT, Baze
University Abuja, Nigeria (email: Jamilu.awwalu@bazeuniversity.edu.ng).
Ali Garba Garba, Anahita Ghazvini, and Rose Atuah are with the Faculty
of Information Science and Technology, Universiti Kebangsaan Malaysia,
43600 Bangi, Selangor Darul Ihsan, Malaysia (e-mail: {aligarba, P72674,
roseatuah}@siswa.ukm.edu.my).
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Cite:Jamilu Awwalu, Ali Garba Garba, Anahita Ghazvini, and Rose Atuah, "Artificial Intelligence in Personalized Medicine Application of AI Algorithms in Solving Personalized Medicine Problems," International Journal of Computer Theory and Engineering vol. 7, no. 6, pp. 439-443, 2015.