Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI
Abstract Cardiovascular disease (CVD) is rising as a significant concern for the healthcare sector around the world. Researchers have applied multiple traditional approaches to making healthcare systems find new solutions for the CVD concern. Artificial Intelligence (AI) and blockchain are emerging...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-96715-y |
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| author | Salman Muneer Sagheer Abbas Asghar Ali Shah Meshal Alharbi Haya Aldossary Areej Fatima Taher M. Ghazal Khan Muhammad Adnan |
| author_facet | Salman Muneer Sagheer Abbas Asghar Ali Shah Meshal Alharbi Haya Aldossary Areej Fatima Taher M. Ghazal Khan Muhammad Adnan |
| author_sort | Salman Muneer |
| collection | DOAJ |
| description | Abstract Cardiovascular disease (CVD) is rising as a significant concern for the healthcare sector around the world. Researchers have applied multiple traditional approaches to making healthcare systems find new solutions for the CVD concern. Artificial Intelligence (AI) and blockchain are emerging approaches that may be integrated into the healthcare sector to help responsible and secure decision-making in dealing with CVD concerns. Secure CVD information is needed while dealing with confidential patient healthcare data, especially with a decentralized blockchain technology (BCT) system that requires strong encryption. However, AI and blockchain-empowered approaches could make people trust the healthcare sector, mainly in diagnosing areas like cardiovascular care. This research proposed an explainable AI (XAI) approach entangled with BCT that enhances healthcare interpretability and responsibility to cardiovascular health medical experts. XAI is significant in addressing cardiovascular prediction issues and offers potential solutions for complex communication and decision-making in cardiovascular care. The proposed approach performs better, with the highest accuracy of 97.12% compared to earlier methods. This achievement shows its ability to tackle complex issues, accessible during healthcare sector communication and decision processes. |
| format | Article |
| id | doaj-art-bb89969a3e1646cc97a5eefb6d7707a7 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-bb89969a3e1646cc97a5eefb6d7707a72025-08-20T01:53:11ZengNature PortfolioScientific Reports2045-23222025-04-0115112410.1038/s41598-025-96715-yResponsible CVD screening with a blockchain assisted chatbot powered by explainable AISalman Muneer0Sagheer Abbas1Asghar Ali Shah2Meshal Alharbi3Haya Aldossary4Areej Fatima5Taher M. Ghazal6Khan Muhammad Adnan7Department of Computer Science, University of Central PunjabDepartment of Computer Science, Prince Mohammad Bin Fahd UniversityDepartment of Computer Science, Kateb UniversityDepartment of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz UniversityComputer Science Department, College of Science and Humanities, Imam Abdulrahman Bin Faisal UniversityDepartment of Computer Science, Lahore Garrison UniversityDepartment of Networks and Cybersecurity, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman UniversityDepartment of Software, Faculty of Artificial Intelligence and Software, Gachon UniversityAbstract Cardiovascular disease (CVD) is rising as a significant concern for the healthcare sector around the world. Researchers have applied multiple traditional approaches to making healthcare systems find new solutions for the CVD concern. Artificial Intelligence (AI) and blockchain are emerging approaches that may be integrated into the healthcare sector to help responsible and secure decision-making in dealing with CVD concerns. Secure CVD information is needed while dealing with confidential patient healthcare data, especially with a decentralized blockchain technology (BCT) system that requires strong encryption. However, AI and blockchain-empowered approaches could make people trust the healthcare sector, mainly in diagnosing areas like cardiovascular care. This research proposed an explainable AI (XAI) approach entangled with BCT that enhances healthcare interpretability and responsibility to cardiovascular health medical experts. XAI is significant in addressing cardiovascular prediction issues and offers potential solutions for complex communication and decision-making in cardiovascular care. The proposed approach performs better, with the highest accuracy of 97.12% compared to earlier methods. This achievement shows its ability to tackle complex issues, accessible during healthcare sector communication and decision processes.https://doi.org/10.1038/s41598-025-96715-yBlockchainChatbotCVD screeningExplainable AI |
| spellingShingle | Salman Muneer Sagheer Abbas Asghar Ali Shah Meshal Alharbi Haya Aldossary Areej Fatima Taher M. Ghazal Khan Muhammad Adnan Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI Scientific Reports Blockchain Chatbot CVD screening Explainable AI |
| title | Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI |
| title_full | Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI |
| title_fullStr | Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI |
| title_full_unstemmed | Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI |
| title_short | Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI |
| title_sort | responsible cvd screening with a blockchain assisted chatbot powered by explainable ai |
| topic | Blockchain Chatbot CVD screening Explainable AI |
| url | https://doi.org/10.1038/s41598-025-96715-y |
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