NDLI: Thyroid disease diagnosis: A survey

Content Provider	IEEE Xplore Digital Library
Author	Shroff, S. Pise, S. Chalekar, P. Panicker, S.S.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Eng., MAEER's MIT, Pune, India (Shroff, S.; Pise, S.; Chalekar, P.; Panicker, S.S.)
Abstract	Diagnosis is an important task in medical science because of its criticality, efficiency and accuracy in determining whether or not a patient has a particular disease. This shall further decide the most suitable line of treatment. There has been a large increase in the number of thyroid cases over the past few years. Since thyroid has a complex relation with metabolism and body weight, it is extremely important to diagnose thyroid disease as early as possible. This paper presents an exhaustive survey of work done in the past with respect to semi-automated medical diagnosis in general and thyroid disease diagnosis in particular. Medical Diagnosis encompassed the use of classifiers like Fuzzy Neural Networks, k-Nearest Neighbor and Decision Tree, while the latter included the use of Computer-Aided Diagnosis, different Neural Networks and Support Vector Machine. Amongst these, the impact of Feature Selection using Particle Swarm Optimization and Ant Colony Optimization on classification was also surveyed.
Starting Page	1
Ending Page	6
File Size	364901
Page Count	6
File Format	PDF
e-ISBN	9781479964802
DOI	10.1109/ISCO.2015.7282384
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-09
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Solid modeling Accuracy Medical Diagnosis Computational modeling Computer Aided Diagnosis Artificial neural networks Classification Thyroid Diagnosis Medical diagnostic imaging
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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
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