Skip to main content

Research Repository

Advanced Search

Welcome to USIR

Welcome to the University of Salford repository (USIR), an Open Access showcase for the published research output of the university. Our collection contains a wide range of research across multiple formats and subject areas.

Whenever possible, outputs will be made openly available here in full digital format for download, with many under a Creative Commons license. See our Policies for further information https://salford-repository.worktribe.com/policies.

Research Outputs

People

Schools

Research Projects



Latest Additions

Pre-treatment assessment of chemotherapy for cancer patients: a multi-site evidence implementation project of 74 hospitals in China (2024)
Journal Article
Lai, J., Pilla, B., Stephenson, M., Brettle, A., Zhou, C., Li, W., …Wu, Y. (in press). Pre-treatment assessment of chemotherapy for cancer patients: a multi-site evidence implementation project of 74 hospitals in China. BMC Nursing, 23(1), 320. https://doi.org/10.1186/s12912-024-01997-8

Background: Chemotherapy, whilst treating tumours, can also lead to numerous adverse reactions such as nausea and vomiting, fatigue and kidney toxicity, threatening the physical and mental health of patients. Simultaneously, misuse of chemotherapeuti... Read More about Pre-treatment assessment of chemotherapy for cancer patients: a multi-site evidence implementation project of 74 hospitals in China.

Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor (2024)
Journal Article
Albalawi, E., T.R., M., Thakur, A., Kumar, V. V., Gupta, M., Khan, S. B., & Almusharraf, A. (in press). Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor. BMC Medical Imaging, 24(1), 110. https://doi.org/10.1186/s12880-024-01261-0

Brain tumor classification using MRI images is a crucial yet challenging task in medical imaging. Accurate diagnosis is vital for effective treatment planning but is often hindered by the complex nature of tumor morphology and variations in imaging.... Read More about Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor.

An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis (2024)
Journal Article
Zhang, Y., Wang, X., Xiu, H., Chen, W., Ma, Y., Wei, G., …Ren, L. (2024). An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, 1757-1766. https://doi.org/10.1109/tnsre.2024.3394618

To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this st... Read More about An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis.

Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol (2024)
Journal Article
Khan, S. B., Kumar, A., Mashat, A., Pruthviraja, D., Imam Rahmani, M. K., & Mathew, J. (in press). Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol. SN Computer Science, 5(5), 546. https://doi.org/10.1007/s42979-024-02778-5

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless se... Read More about Artificial Intelligence in Next-Generation Networking: Energy Efficiency Optimization in IoT Networks Using Hybrid LEACH Protocol.