Benchmarked pterygium images for human and machine graders

Che Azemin, Mohd Zulfaezal and Abdul Gaffur, Norfazrina and Hilmi, Mohd Radzi and Mohd Tamrin, Mohd Izzudin and Mohd. Kamal, Khairidzan (2016) Benchmarked pterygium images for human and machine graders. Journal of Engineering and Applied Sciences, 11 (11). pp. 2378-2382. ISSN 1816-949X

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Abstract

In the absence of ground truth, scores from many graders are required to obtain good representation of a clinical grading. The internet enables quick feedback from the experts at the comfort of their home of office. In this study, we demonstrated the use of online form as a tool to get quick feedback from clinicians on clinical grading of pterygium images with various severities. The scores were analyzed using quartile analysis and the median was used to construct the benchmark scores for the images. This dataset was tested on assessing human grader and was later fitted with neural network to measure the performance of the machine learning algorithm.

Item Type:	Article (Journal)
Additional Information:	6768/54743
Uncontrolled Keywords:	Machine learning, benchmarked dataset, ground truth, quick feedback, Malaysia
Subjects:	R Medicine > RE Ophthalmology T Technology > TA Engineering (General). Civil engineering (General) > TA329 Engineering mathematics. Engineering analysis
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Allied Health Sciences Kulliyyah of Allied Health Sciences > Department of Audiology and Speech-Language Pathology
Depositing User:	Dr. Mohd Zulfaezal Che Azemin
Date Deposited:	01 Feb 2017 15:00
Last Modified:	30 Jun 2022 15:29
URI:	http://irep.iium.edu.my/id/eprint/54743

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