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Cross-checked screening application for reliable categorisation of familial hypercholesterolaemia: design and development of the prototype
IAES International Journal of Artificial Intelligence · Vol. 12 No. 2 (2023) · hlm. 704–713
ISSN 2252-8938, 2089-4872
Terbit 2023-06-01
Penerbit Institute of Advanced Engineering and Science
Bahasa eng
Abstrak
The paper describes the development of a computer-based familial hypercholesterolemia (FH) screening application (FH CatScreen©). The application facilitates automatic scoring and categorisation of patients by medical practitioners based on four well-known FH diagnostic criteria. In the absence of a FH diagnostic criterion for Malaysian population, these four diagnostic criteria are commonly used criteria to classify patients FH severity levels to manage early interventions. We applied an adaptive software development approach comprising planning, development and validation phases to develop FH CatScreen©. A user study involving thirty medical practitioners was conducted to evaluate the effectiveness and usability of FH CatScreen©. The study showed that FH CatScreen© was able to provide a more correct, faster and better-informed assessment compared to the traditional paper-based method. The study further showed that FH CatScreen© has a good degree of performance and acceptance by the participants. The participants indicated that the simultaneous use of the four diagnostic criteria in FH CatScreen© has assisted them to compare the outcomes of each of the criterion side-by-side. It allowed them to decide on the severity of patient condition with high confidence. FH CatScreen© has demonstrated its expediency and efficacy in collecting the data on FH incidence and prevalence in Malaysia.
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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title xml:lang="en-US">Cross-checked screening application for reliable categorisation of familial hypercholesterolaemia: design and development of the prototype</dc:title>
<dc:creator>Rosli, Marshima Mohd</dc:creator>
<dc:creator>Annamalai, Muthukkaruppan</dc:creator>
<dc:creator>Mohd Kasim, Noor Alicezah</dc:creator>
<dc:creator>Yung-An, Chua</dc:creator>
<dc:creator>Nawawi, Hapizah Mohd</dc:creator>
<dc:subject xml:lang="en-US">Information System; Rule Based Algorithm</dc:subject>
<dc:subject xml:lang="en-US">Automated scoring and categorisation application; Familial hypercholesterolemia; Familial hypercholesterolemia diagnostic criteria</dc:subject>
<dc:description xml:lang="en-US">The paper describes the development of a computer-based familial hypercholesterolemia (FH) screening application (FH CatScreen©). The application facilitates automatic scoring and categorisation of patients by medical practitioners based on four well-known FH diagnostic criteria. In the absence of a FH diagnostic criterion for Malaysian population, these four diagnostic criteria are commonly used criteria to classify patients FH severity levels to manage early interventions. We applied an adaptive software development approach comprising planning, development and validation phases to develop FH CatScreen©. A user study involving thirty medical practitioners was conducted to evaluate the effectiveness and usability of FH CatScreen©. The study showed that FH CatScreen© was able to provide a more correct, faster and better-informed assessment compared to the traditional paper-based method. The study further showed that FH CatScreen© has a good degree of performance and acceptance by the participants. The participants indicated that the simultaneous use of the four diagnostic criteria in FH CatScreen© has assisted them to compare the outcomes of each of the criterion side-by-side. It allowed them to decide on the severity of patient condition with high confidence. FH CatScreen© has demonstrated its expediency and efficacy in collecting the data on FH incidence and prevalence in Malaysia.</dc:description>
<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
<dc:contributor xml:lang="en-US"></dc:contributor>
<dc:date>2023-06-01</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:type xml:lang="en-US"></dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/21642</dc:identifier>
<dc:identifier>10.11591/ijai.v12.i2.pp704-713</dc:identifier>
<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 12, No 2: June 2023; 704-713</dc:source>
<dc:source>2252-8938</dc:source>
<dc:source>2089-4872</dc:source>
<dc:source>10.11591/ijai.v12.i2</dc:source>
<dc:language>eng</dc:language>
<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/21642/13634</dc:relation>
<dc:rights xml:lang="en-US">Copyright (c) 2022 Institute of Advanced Engineering and Science</dc:rights>
<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>
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APA 7
Rosli, M. M., Annamalai, M., Mohd Kasim, N. A., Yung-An, C., & Nawawi, H. M. (2023). Cross-checked screening application for reliable categorisation of familial hypercholesterolaemia: design and development of the prototype. IAES International Journal of Artificial Intelligence, 12(2), 704–713. https://doi.org/10.11591/ijai.v12.i2.pp704-713
Salin
IEEE
M. M. Rosli, M. Annamalai, N. A. Mohd Kasim, C. Yung-An, and H. M. Nawawi, “Cross-checked screening application for reliable categorisation of familial hypercholesterolaemia: design and development of the prototype,” IAES International Journal of Artificial Intelligence, vol. 12, no. 2, pp. 704–713, 2023, doi: 10.11591/ijai.v12.i2.pp704-713.
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