Improving the Computational Complexity of the COOL Screening Tool
Autoimmune disorder, such as celiac disease and type 1 diabetes, is a condition in which the immune system attacks body tissues by mistake. This might be triggered by abnormality in the development of biomarkers such as autoantibodies, which are generated by unhealthy beta cells. Therefore, screenin...
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| Vydáno v: | International journal of advanced computer science & applications Ročník 13; číslo 5 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
West Yorkshire
Science and Information (SAI) Organization Limited
2022
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| Témata: | |
| ISSN: | 2158-107X, 2156-5570 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Autoimmune disorder, such as celiac disease and type 1 diabetes, is a condition in which the immune system attacks body tissues by mistake. This might be triggered by abnormality in the development of biomarkers such as autoantibodies, which are generated by unhealthy beta cells. Therefore, screening of such biomarkers is crucial for early diagnosis of autoimmune diseases. However, one of the fundamental questions of screening is when to screen subjects who might be at a higher risk of au-toimmune disorder. This requires an exhaustive search to find the optimal ages of screening in retrospective cohorts. Very recently, a comprehensive tool was developed for screening in autoimmune disease. In this paper, we improved the computational time of the algorithm used in the screening tool. The new algorithm is more than 100 times faster than the original one. This improvement would help to increase the utility of the tool among clinicians and research scientists in the community. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2158-107X 2156-5570 |
| DOI: | 10.14569/IJACSA.2022.01305114 |