NDLI: Computational Intelligence for HIV Modelling

Content Provider	IEEE Xplore Digital Library
Author	Betechuoh, B.L. Marwala, T. Manana, J.V.
Copyright Year	2008
Description	Author affiliation: Sch. of Electr. & Inf. Eng., Univ. of Witwatersrand, Johannesburg (Betechuoh, B.L.; Marwala, T.)
Abstract	In this paper, we compare computational intelligence methods to analyze HIV in order to investigate which network is best suited for HIV classification. The methods analyzed are autoencoder multi-layer perceptron (MLP), autoencoder radial basis functions (RBF), support vector machines (SVM) and neuro-fuzzy models (NFM). The autoencoder multi-layer perceptron yields the highest accuracy of 92% amongst all the models studied. The autoencoder radial basis function model has the shortest computational time but yields one of the lowest accuracies of 82%. The SVM model yields the worst accuracy of 80%, as well as the worst computational time of 203s. The NFM yields an accuracy of 86%, which is the second highest accuracy. The NFM, however, offers rules, which gives interpretation of the data. The area under the receiver operating characteristics curve for the MLP model is 0.86 compared to an area under the curve of 0.87 for the RBF model, and 0.82 for the neuro- fuzzy model. The autoencoder MLP network model for HIV classification, is thus found to outperform the other network models and is a much better classifier.
Starting Page	127
Ending Page	132
File Size	482540
Page Count	6
File Format	PDF
ISBN	9781424420827
DOI	10.1109/INES.2008.4481281
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-02-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational intelligence Human immunodeficiency virus Biological neural networks Support vector machines Demography Multilayer perceptrons Acquired immune deficiency syndrome Mathematical model Diseases Immune system
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	ndl-support@iitkgp.ac.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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