Optimizing Heart Attack Detection with Brown-Bear Optimization Algorithm and CNN in Healthcare 4.0 Article Swipe
Akshat Gaurav
,
Brij B. Gupta
,
Jinsong Wu
,
Varsha Arya
,
Priyanka Chaurasia
,
Kwok Tai Chui
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/gcwkshp64532.2024.11101658
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/gcwkshp64532.2024.11101658
Heart disease is a non-communicable decease that lead to death if not treated. In the world most of the people died due to heart disease because they are not treated on time or their disease is not detected at early stage. Due to this efficient heart disease prediction techniques are important for the development of Healthcare 4.0. However, most of the current heart disease detection algorithms are either complex or not optimizes for efficient hyper-parameters. In this context, we proposed a CNN based lightweight heart disease detection framework (trained in 5 epoch). We also used random forest algorithm to identify the most important feature and Brown-Bear Algorithm for optimization of the hyper-parameter of CNN. We also compared the proposed model with current literature and present the efficiency of our proposed framework.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/gcwkshp64532.2024.11101658
- OA Status
- green
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413180104
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413180104Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/gcwkshp64532.2024.11101658Digital Object Identifier
- Title
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Optimizing Heart Attack Detection with Brown-Bear Optimization Algorithm and CNN in Healthcare 4.0Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-08Full publication date if available
- Authors
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Akshat Gaurav, Brij B. Gupta, Jinsong Wu, Varsha Arya, Priyanka Chaurasia, Kwok Tai ChuiList of authors in order
- Landing page
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https://doi.org/10.1109/gcwkshp64532.2024.11101658Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://pure.ulster.ac.uk/en/publications/adfee4a1-1a72-4d79-9c7e-d691b5b3d50cDirect OA link when available
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Computer science, Health care, Optimization algorithm, Algorithm, Artificial intelligence, Mathematical optimization, Mathematics, Economic growth, EconomicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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18Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.with | 120 |
| abstract_inverted_index.Heart | 0 |
| abstract_inverted_index.based | 82 |
| abstract_inverted_index.death | 9 |
| abstract_inverted_index.early | 39 |
| abstract_inverted_index.heart | 23, 45, 62, 84 |
| abstract_inverted_index.model | 119 |
| abstract_inverted_index.their | 33 |
| abstract_inverted_index.world | 15 |
| abstract_inverted_index.either | 67 |
| abstract_inverted_index.forest | 96 |
| abstract_inverted_index.people | 19 |
| abstract_inverted_index.random | 95 |
| abstract_inverted_index.stage. | 40 |
| abstract_inverted_index.because | 25 |
| abstract_inverted_index.complex | 68 |
| abstract_inverted_index.current | 61, 121 |
| abstract_inverted_index.decease | 5 |
| abstract_inverted_index.disease | 1, 24, 34, 46, 63, 85 |
| abstract_inverted_index.epoch). | 91 |
| abstract_inverted_index.feature | 103 |
| abstract_inverted_index.present | 124 |
| abstract_inverted_index.treated | 29 |
| abstract_inverted_index.(trained | 88 |
| abstract_inverted_index.However, | 57 |
| abstract_inverted_index.compared | 116 |
| abstract_inverted_index.context, | 77 |
| abstract_inverted_index.detected | 37 |
| abstract_inverted_index.identify | 99 |
| abstract_inverted_index.proposed | 79, 118, 129 |
| abstract_inverted_index.treated. | 12 |
| abstract_inverted_index.Algorithm | 106 |
| abstract_inverted_index.algorithm | 97 |
| abstract_inverted_index.detection | 64, 86 |
| abstract_inverted_index.efficient | 44, 73 |
| abstract_inverted_index.framework | 87 |
| abstract_inverted_index.important | 50, 102 |
| abstract_inverted_index.optimizes | 71 |
| abstract_inverted_index.Brown-Bear | 105 |
| abstract_inverted_index.Healthcare | 55 |
| abstract_inverted_index.algorithms | 65 |
| abstract_inverted_index.efficiency | 126 |
| abstract_inverted_index.framework. | 130 |
| abstract_inverted_index.literature | 122 |
| abstract_inverted_index.prediction | 47 |
| abstract_inverted_index.techniques | 48 |
| abstract_inverted_index.development | 53 |
| abstract_inverted_index.lightweight | 83 |
| abstract_inverted_index.optimization | 108 |
| abstract_inverted_index.hyper-parameter | 111 |
| abstract_inverted_index.non-communicable | 4 |
| abstract_inverted_index.hyper-parameters. | 74 |
| cited_by_percentile_year | |
| countries_distinct_count | 5 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.47360209 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |