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...

Full description

Saved in:
Bibliographic Details
Main Authors: Salman Muneer, Sagheer Abbas, Asghar Ali Shah, Meshal Alharbi, Haya Aldossary, Areej Fatima, Taher M. Ghazal, Khan Muhammad Adnan
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-96715-y
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850269255758512128
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
work_keys_str_mv AT salmanmuneer responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT sagheerabbas responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT asgharalishah responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT meshalalharbi responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT hayaaldossary responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT areejfatima responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT tahermghazal responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai
AT khanmuhammadadnan responsiblecvdscreeningwithablockchainassistedchatbotpoweredbyexplainableai