Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Blockchain-Enabled healthcare system for detection of diabetes
AU - Chen, Mengji
AU - Malook, Taj
AU - Rehman, Ateeq Ur
AU - Muhammad, Yar
AU - Alshehri, Mohammad Dahman
AU - Akbar, Aamir
AU - Bilal, Muhammad
AU - Khan, Muazzam A.
PY - 2021/5/31
Y1 - 2021/5/31
N2 - Blockchain has penetrated numerous domains such as, industries, government agencies, online voting, and healthcare, etc. Among these domains, healthcare is one of the trending and most important one, which consists of a control system and an Electronic Health Records (EHRs). Diabetes is one of the most rapidly growing chronic diseases that increases the death ratio across the globe. This paper presents a Blockchain-enabled diabetes disease detection framework that provides an earlier detection of this disease by using various machine learning classification algorithms and maintains the EHRs of the patients in a secure manner. Our EHRs sharing framework combines symptom-based disease prediction, Blockchain, and interplanetary file system (IPFS) in which the patient's health information are collected via wearable sensor devices. This information is then sent to EHRs manager, where an ML model is executed for further processing to collect the desired results. The results along with the physiological parameters are then stored in the Blockchain with the approval of concerned patient and his/her practitioner. It is anticipated that our proposed system will help the healthcare society in order to store, process, and share the patient health information in a secure manner.
AB - Blockchain has penetrated numerous domains such as, industries, government agencies, online voting, and healthcare, etc. Among these domains, healthcare is one of the trending and most important one, which consists of a control system and an Electronic Health Records (EHRs). Diabetes is one of the most rapidly growing chronic diseases that increases the death ratio across the globe. This paper presents a Blockchain-enabled diabetes disease detection framework that provides an earlier detection of this disease by using various machine learning classification algorithms and maintains the EHRs of the patients in a secure manner. Our EHRs sharing framework combines symptom-based disease prediction, Blockchain, and interplanetary file system (IPFS) in which the patient's health information are collected via wearable sensor devices. This information is then sent to EHRs manager, where an ML model is executed for further processing to collect the desired results. The results along with the physiological parameters are then stored in the Blockchain with the approval of concerned patient and his/her practitioner. It is anticipated that our proposed system will help the healthcare society in order to store, process, and share the patient health information in a secure manner.
KW - Blockchain
KW - Classification algorithms
KW - Diabetes disease
KW - Healthcare
KW - Secure systems
U2 - 10.1016/j.jisa.2021.102771
DO - 10.1016/j.jisa.2021.102771
M3 - Journal article
AN - SCOPUS:85100619623
VL - 58
JO - Journal of Information Security and Applications
JF - Journal of Information Security and Applications
SN - 2214-2134
M1 - 102771
ER -