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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) · pp. 704–713

DOI
10.11591/ijai.v12.i2.pp704-713
ISSN
2252-8938, 2089-4872
Published
2023-06-01
Publisher
Institute of Advanced Engineering and Science
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

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.

Keywords

Collaboration network of the authors

13 authors · 25 co-authorship links

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  • Universiti Teknologi MARA
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Muhammad Izzuddin Mohd SaniAffiliation unknown1
Nur Atiqah Sia AbdullahUniversiti Teknologi MARA1
Nor Shahida Mohamad YusopUniversiti Teknologi MARA1
Xiaoling GaoUniversiti Teknologi MARA1
Muhammad Izzad RamliUniversiti Teknologi MARA1
Nursuriati JamilUniversiti Teknologi MARA1
Syed Mohd Zahid Syed Zainal AriffinUniversiti Teknologi MARA1
Siti Nur Shahidah Zaman ShahAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<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>