Application of higher-order spectra for automated grading of diabetic maculopathy Article Swipe

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Muthu Rama Krishnan Mookiah , U. Rajendra Acharya , Vinod Chandran , Roshan Joy Martis , Jen Hong Tan , Joel E.W. Koh , Chua Kuang Chua , Louis Tong , Augustinus Laude ·

YOU? · · 2015 · Open Access · · DOI: https://doi.org/10.1007/s11517-015-1278-7

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Artificial Intelligence

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Artificial intelligence Pattern recognition (psychology) Bispectrum Linear discriminant analysis Fundus (uterus) Mathematics Ophthalmology Computer science Medicine Statistics Spectral density

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Type: article
Language: en
Landing Page: https://doi.org/10.1007/s11517-015-1278-7
OA Status: green
Cited By: 1
References: 40
Related Works: 20
OpenAlex ID: https://openalex.org/W1504370999

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OpenAlex ID: https://openalex.org/W1504370999

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DOI: https://doi.org/10.1007/s11517-015-1278-7

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Title: Application of higher-order spectra for automated grading of diabetic maculopathy

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Type: article

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Language: en

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Publication year: 2015

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Publication date: 2015-04-17

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Authors: Muthu Rama Krishnan Mookiah, U. Rajendra Acharya, Vinod Chandran, Roshan Joy Martis, Jen Hong Tan, Joel E.W. Koh, Chua Kuang Chua, Louis Tong, Augustinus Laude

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Landing page: https://doi.org/10.1007/s11517-015-1278-7

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Open access: Yes

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OA status: green

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OA URL: https://eprints.qut.edu.au/84131/7/84131.pdf

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Concepts: Artificial intelligence, Pattern recognition (psychology), Bispectrum, Linear discriminant analysis, Fundus (uterus), Mathematics, Ophthalmology, Computer science, Medicine, Statistics, Spectral density

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Cited by: 1

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References (count): 40

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referenced_works	https://openalex.org/W2077176021, https://openalex.org/W114328460, https://openalex.org/W167879504, https://openalex.org/W2065385897, https://openalex.org/W2106253207, https://openalex.org/W2166603076, https://openalex.org/W2114755071, https://openalex.org/W2155610576, https://openalex.org/W2163676538, https://openalex.org/W2149322659, https://openalex.org/W2142841865, https://openalex.org/W1967277574, https://openalex.org/W2107941496, https://openalex.org/W2010962711, https://openalex.org/W2091707840, https://openalex.org/W2021662144, https://openalex.org/W2014287690, https://openalex.org/W1988790447, https://openalex.org/W2055317842, https://openalex.org/W4242028268, https://openalex.org/W2074393399, https://openalex.org/W2044150814, https://openalex.org/W2092728879, https://openalex.org/W1998090164, https://openalex.org/W2169736040, https://openalex.org/W2540782627, https://openalex.org/W1995023030, https://openalex.org/W2123879611, https://openalex.org/W2159764117, https://openalex.org/W2043492194, https://openalex.org/W2062211618, https://openalex.org/W2059579167, https://openalex.org/W2004406940, https://openalex.org/W2060452408, https://openalex.org/W1986086122, https://openalex.org/W2089441731, https://openalex.org/W2543991396, https://openalex.org/W2107983919, https://openalex.org/W4230674625, https://openalex.org/W2138480916
referenced_works_count	40
abstract_inverted_index
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cited_by_percentile_year.min	90
countries_distinct_count	0
institutions_distinct_count	9
citation_normalized_percentile.value	0.04448347
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False