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Bizimana PC, Zhang Z, Hounye AH, Asim M, Hammad M, El-Latif AAA. Automated heart disease prediction using improved explainable learning-based technique. Neural Comput Appl 2024. [DOI: 10.1007/s00521-024-09967-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 05/03/2024] [Indexed: 07/23/2024]
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Bizimana PC, Zhang Z, Asim M, El-Latif AAA, Hammad M. Learning-based techniques for heart disease prediction: a survey of models and performance metrics. MULTIMEDIA TOOLS AND APPLICATIONS 2023; 83:39867-39921. [DOI: 10.1007/s11042-023-17051-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/14/2023] [Accepted: 09/11/2023] [Indexed: 07/23/2024]
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Blockchain-Based Secure Traceable Scheme for Food Supply Chain. J FOOD QUALITY 2023. [DOI: 10.1155/2023/4728840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
The typical food traceability system’s data layer is made up of relational databases managed by core businesses, which cannot ensure data security. It is inefficient and requires a lot of upkeep. The food supply chain has numerous actors, making it difficult for consumers to safeguard their rights when purchasing food with quality issues. Due to the numerous organizations involved in the food supply chain, food safety monitoring and traceability have become challenging. The supply chain’s major organizations have control and administrative authority over the data under the current food traceability system, which is overly centralized for traceability information. The safety and dependability of food may be ensured by using the food traceability system to track food information. We can witness a series of detailed insights into food from the manufacturing source to the consumption terminal. A blockchain-based food tracking system is created as a solution to these issues. On the Ethereum platform, the system was created. It was also employed in the blockchain system, in addition to its features of decentralization, tamper-proof, and traceability. To implement the data update service and the food recall function, introduce the Food and Drug Administration node. Consumers have the option to not only enquire about food traceability throughout the manufacturing process but also to file complaints regarding the traceability system’s rights protection.
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Subhashini P, De Britto C J, Babu KU, Sumathy G. Artificial intelligence for the identification of healthy fruits and vegetables using MMDL-ABO. J EXP THEOR ARTIF IN 2023. [DOI: 10.1080/0952813x.2023.2166592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Affiliation(s)
- P. Subhashini
- Department of IT, Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India
| | | | - K. Upendra Babu
- Department of CSE, Bharath Institute of Higher Education and Research, Chennai, India
| | - G. Sumathy
- Department of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur, India
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