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Comparison of Semi-...
Comparison of Semi-Quantitative Scoring and Artificial Intelligence Aided Digital Image Analysis of Chromogenic Immunohistochemistry
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- Bencze, Janos (författare)
- Univ Debrecen, Div Radiol & Imaging Sci, Dept Med Imaging, Fac Med, H-4032 Debrecen, Hungary.;Univ Debrecen, Dept Neurol, ELKH DE Cerebrovasc & Neurodegenerat Res Grp, H-4032 Debrecen, Hungary.
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- Szarka, Mate (författare)
- Univ Debrecen, Fac Med, Res Ctr Mol Med, Horvath Csaba Lab Bioseparat Sci, H-4032 Debrecen, Hungary.;Vitrolink Kft, H-4033 Debrecen, Hungary.;Inst Nucl Res, H-4026 Debrecen, Hungary.
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- Koti, Balazs (författare)
- Vitrolink Kft, H-4033 Debrecen, Hungary.
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- Seo, Woosung (författare)
- Uppsala universitet,Radiologi
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- Hortobagyi, Tibor G. G. (författare)
- Univ Szeged, Inst Pathol, Albert Szent Gyorgyi Med Sch, H-6725 Szeged, Hungary.
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- Bencs, Viktor (författare)
- Univ Debrecen, Dept Neurol, Fac Med, H-4032 Debrecen, Hungary.
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- Modis, Laszlo V. (författare)
- Univ Debrecen, Dept Behav Sci, Fac Med, H-4032 Debrecen, Hungary.
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- Hortobagyi, Tibor (författare)
- Univ Debrecen, Dept Neurol, ELKH DE Cerebrovasc & Neurodegenerat Res Grp, H-4032 Debrecen, Hungary.;Univ Szeged, Inst Pathol, Albert Szent Gyorgyi Med Sch, H-6725 Szeged, Hungary.;Kings Coll London, Inst Psychiat Psychol & Neurosci, Dept Old Age Psychiat, London SE5 8AF, England.;Stavanger Univ Hosp, Ctr Age Related Med, SESAM, N-4011 Stavanger, Norway.
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Univ Debrecen, Div Radiol & Imaging Sci, Dept Med Imaging, Fac Med, H-4032 Debrecen, Hungary;Univ Debrecen, Dept Neurol, ELKH DE Cerebrovasc & Neurodegenerat Res Grp, H-4032 Debrecen, Hungary. Univ Debrecen, Fac Med, Res Ctr Mol Med, Horvath Csaba Lab Bioseparat Sci, H-4032 Debrecen, Hungary.;Vitrolink Kft, H-4033 Debrecen, Hungary.;Inst Nucl Res, H-4026 Debrecen, Hungary. (creator_code:org_t)
- 2021-12-23
- 2022
- Engelska.
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Ingår i: Biomolecules. - : MDPI AG. - 2218-273X. ; 12
- Relaterad länk:
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https://uu.diva-port... (primary) (Raw object)
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https://www.mdpi.com...
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https://urn.kb.se/re...
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https://doi.org/10.3...
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Abstract
Ämnesord
Stäng
- Semi-quantitative scoring is a method that is widely used to estimate the quantity of proteins on chromogen-labelled immunohistochemical (IHC) tissue sections. However, it suffers from several disadvantages, including its lack of objectivity and the fact that it is a time-consuming process. Our aim was to test a recently established artificial intelligence (AI)-aided digital image analysis platform, Pathronus, and to compare it to conventional scoring by five observers on chromogenic IHC-stained slides belonging to three experimental groups. Because Pathronus operates on grayscale 0-255 values, we transformed the data to a seven-point scale for use by pathologists and scientists. The accuracy of these methods was evaluated by comparing statistical significance among groups with quantitative fluorescent IHC reference data on subsequent tissue sections. The pairwise inter-rater reliability of the scoring and converted Pathronus data varied from poor to moderate with Cohen's kappa, and overall agreement was poor within every experimental group using Fleiss' kappa. Only the original and converted that were obtained from Pathronus original were able to reproduce the statistical significance among the groups that were determined by the reference method. In this study, we present an AI-aided software that can identify cells of interest, differentiate among organelles, protein specific chromogenic labelling, and nuclear counterstaining after an initial training period, providing a feasible and more accurate alternative to semi-quantitative scoring.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
Nyckelord
- artificial intelligence (AI)
- digital image analysis
- immunohistochemistry
- semi-quantitative scoring
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- ref (ämneskategori)
- art (ämneskategori)
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