Top cited documents
| Author (Year) | Citations | Area of research | Insights |
|---|---|---|---|
| Sarker (2021a) | 2,596 | Machine Learning (ML) | Explored ML algorithms and real-world applications in Industry 4.0; discussed challenges and future directions in healthcare adoption |
| Fuller et al. (2020) | 1,396 | Digital Twin (DT) | Examined enabling technologies and challenges of DT in healthcare; highlighted the impact on predictive maintenance and operational efficiency |
| Aceto et al. (2020) | 672 | IoT, Big Data, Blockchain | Proposed a framework for integrating IoT, big data, and blockchain to improve healthcare services |
| Sengupta et al. (2020) | 653 | IoT Security | Surveyed security issues and attacks in IoT-based healthcare systems, focusing on encryption and authentication mechanisms |
| Kumari et al. (2018) | 423 | Fog Computing | Explored fog computing in healthcare; proposed a hybrid model to handle real-time data processing and reduce latency |
| Pace et al. (2019) | 350 | Edge Computing | Discussed an edge-based architecture for efficient and secure data transmission that supports real-time healthcare operations |
| Elhoseny et al. (2018) | 281 | IoT and Cloud Computing | Proposed a hybrid model combining IoT and cloud computing that focuses on improving healthcare service delivery and real-time data processing |
| Sarker (2021b) | 247 | Data Science and Analytics | Provided an overview of data science and analytics in healthcare; emphasized predictive insights for transforming healthcare systems |
| Ding (2018) | 245 | I4.0 in Pharma | Reviewed the adoption of Industry 4.0 in the pharmaceutical industry; focused on improving drug manufacturing processes |
| Attaran and Celik (2023) | 241 | Digital Twin (DT) | Explored the benefits, challenges, and future use cases of DT in healthcare; highlighted enhanced patient care and operational efficiency |
| Author (Year) | Citations | Area of research | Insights |
|---|---|---|---|
| 2,596 | Machine Learning (ML) | Explored ML algorithms and real-world applications in Industry 4.0; discussed challenges and future directions in healthcare adoption | |
| 1,396 | Digital Twin (DT) | Examined enabling technologies and challenges of DT in healthcare; highlighted the impact on predictive maintenance and operational efficiency | |
| 672 | IoT, Big Data, Blockchain | Proposed a framework for integrating IoT, big data, and blockchain to improve healthcare services | |
| 653 | IoT Security | Surveyed security issues and attacks in IoT-based healthcare systems, focusing on encryption and authentication mechanisms | |
| 423 | Fog Computing | Explored fog computing in healthcare; proposed a hybrid model to handle real-time data processing and reduce latency | |
| 350 | Edge Computing | Discussed an edge-based architecture for efficient and secure data transmission that supports real-time healthcare operations | |
| 281 | IoT and Cloud Computing | Proposed a hybrid model combining IoT and cloud computing that focuses on improving healthcare service delivery and real-time data processing | |
| 247 | Data Science and Analytics | Provided an overview of data science and analytics in healthcare; emphasized predictive insights for transforming healthcare systems | |
| 245 | I4.0 in Pharma | Reviewed the adoption of Industry 4.0 in the pharmaceutical industry; focused on improving drug manufacturing processes | |
| 241 | Digital Twin (DT) | Explored the benefits, challenges, and future use cases of DT in healthcare; highlighted enhanced patient care and operational efficiency |
Source(s): Authors’ own creation/work