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Integration of Blockchain and Cloud Computing in Telemedicine and Healthcare
Asma Albassam,Fatima Almutairi,Nouf Majoun,Reem Althukair,Zahra Alturaiki,Atta Rahman,Dania AlKhulaifi,Maqsood Mahmud International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.6
Blockchain technology has emerged as one of the most crucial solutions in numerous industries, including healthcare. The combination of blockchain technology and cloud computing results in improving access to high-quality telemedicine and healthcare services. In addition to developments in healthcare, the operational strategy outlined in Vision 2030 is extremely essential to the improvement of the standard of healthcare in Saudi Arabia. The purpose of this survey is to give a thorough analysis of the current state of healthcare technologies that are based on blockchain and cloud computing. We highlight some of the unanswered research questions in this rapidly expanding area and provide some context for them. Furthermore, we demonstrate how blockchain technology can completely alter the medical field and keep health records private; how medical jobs can detect the most critical, dangerous errors with blockchain industries. As it contributes to develop concerns about data manipulation and allows for a new kind of secure data storage pattern to be implemented in healthcare especially in telemedicine fields is discussed diagrammatically.
Diabetes Detection and Forecasting using Machine Learning Approaches: Current State-of-the-art
Alwalid Alhashem,Aiman Abdulbaset,Faisal Almudarra,Hazzaa Alshareef,Mshari Alqasoumi,Atta-ur Rahman,Maqsood Mahmud International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.10
The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.