Computer-aided diagnosis of thyroid malignancy using an artificial immune system classification algorithm

Delibasis, KK; Asvestas, PA; Matsopoulos, GK; Zoulias, E; Tseleni-Balafouta, S

dc.contributor.author	Delibasis, KK	en
dc.contributor.author	Asvestas, PA	en
dc.contributor.author	Matsopoulos, GK	en
dc.contributor.author	Zoulias, E	en
dc.contributor.author	Tseleni-Balafouta, S	en
dc.date.accessioned	2014-03-01T01:30:00Z
dc.date.available	2014-03-01T01:30:00Z
dc.date.issued	2009	en
dc.identifier.issn	1089-7771	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19450
dc.subject	Artificial immune systems (AIS)	en
dc.subject	Classification	en
dc.subject	Feature selection	en
dc.subject	Fine needle aspiration (FNA)	en
dc.subject	Thyroid malignancy	en
dc.subject	Yhyroid malignancy	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Mathematical & Computational Biology	en
dc.subject.classification	Medical Informatics	en
dc.subject.other	algorithm	en
dc.subject.other	article	en
dc.subject.other	artificial intelligence	en
dc.subject.other	biological model	en
dc.subject.other	classification	en
dc.subject.other	computer assisted diagnosis	en
dc.subject.other	human	en
dc.subject.other	immunology	en
dc.subject.other	methodology	en
dc.subject.other	needle biopsy	en
dc.subject.other	receiver operating characteristic	en
dc.subject.other	thyroid nodule	en
dc.subject.other	thyroid tumor	en
dc.subject.other	Algorithms	en
dc.subject.other	Artificial Intelligence	en
dc.subject.other	Biopsy, Fine-Needle	en
dc.subject.other	Diagnosis, Computer-Assisted	en
dc.subject.other	Humans	en
dc.subject.other	Models, Immunological	en
dc.subject.other	ROC Curve	en
dc.subject.other	Thyroid Neoplasms	en
dc.subject.other	Thyroid Nodule	en
dc.subject.other	Artificial immune systems (AIS)	en
dc.subject.other	Classification	en
dc.subject.other	Feature selection	en
dc.subject.other	Fine needle aspiration (FNA)	en
dc.subject.other	Thyroid malignancy	en
dc.subject.other	Yhyroid malignancy	en
dc.subject.other	Algorithms	en
dc.subject.other	Immunology	en
dc.subject.other	Mathematical operators	en
dc.subject.other	Needles	en
dc.subject.other	Sensitivity analysis	en
dc.subject.other	Computer aided diagnosis	en
dc.title	Computer-aided diagnosis of thyroid malignancy using an artificial immune system classification algorithm	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TITB.2008.926990	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TITB.2008.926990	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	The diagnosis of thyroid malignancy by fine needle aspiration (FNA) examination has been proven to show wide variations of sensitivity and specificity. This paper proposes the utilization of a computer-aided diagnosis system based on a supervised classification algorithm from the artificial immune systems to assist the task of thyroid malignancy diagnosis. The core of the proposed algorithm is the so-called BoxCells, which are defined as parallelepipeds in the feature space. Properly defined operators act on the BoxCells in order to convert them into individual, elementary classifiers. The proposed algorithm is applied on FNA data from 2016 subjects with verified diagnosis and has exhibited average specificity higher than 99%, 90% sensitivity, and 98.5% accuracy. Furthermore, 24% of the cases that are characterized as ""suspicious"" by FNA and are histologically proven nonmalignancies have been classified correctly. © 2009 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Information Technology in Biomedicine	en
dc.identifier.doi	10.1109/TITB.2008.926990	en
dc.identifier.isi	ISI:000269518900003	en
dc.identifier.volume	13	en
dc.identifier.issue	5	en
dc.identifier.spage	680	en
dc.identifier.epage	686	en