Staff Profile
Saleh Mohamed
Research Associate, Health Data Science, NIHR Innovation Observatory
- Email: saleh.mohamed@ncl.ac.uk
- Address: NIHR Innovation Observatory
Room 3.12, The Catalyst
3 Science Square
Newcastle Helix
Newcastle upon Tyne
United Kingdom
NE4 5TG
Saleh is a Research Associate in Health Data Science at the NIHR Innovation Observatory. With a background in information retrieval and natural language processing, his work focuses on leveraging advanced computational techniques to address challenges in healthcare innovation.
His research interests lie at the intersection of artificial intelligence and healthcare, with a particular emphasis on applying machine learning and deep learning to identify and monitor emerging trends, technologies, and advancements in the healthcare sector.
About the NIHR Innovation Observatory
Home - NIHR Innovation Observatory
The NIHR Innovation Observatory is a world-leading health and care innovation scanning centre providing data-driven insights to foster innovation and equitable access to high-quality care. We aim to transform health systems and improve population health by providing advanced data-driven insights that foster innovation and equitable access to high-quality care. At the core of our work, is the development of data-driven methods to identify, capture, and synthesize intelligence on new health innovations. We develop and share cutting-edge methods in horizon scanning, building capacity in the systems across the public, voluntary and industry sectors.
We deliver essential intelligence and insights about medicines and MedTech innovation to the National Institute of Health and Care Excellence (NICE) and NHS England (NHSE), as well as the Medicines and Healthcare Products Regulatory Agency (MHRA), the NIHR, the UK Health Security Agency (UKHSA), DHSC and industry - allowing these organisations to prepare for policies, regulation and frontline delivery for new, emerging and disruptive technologies.
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Conference Proceedings (inc. Abstracts)
- Mohamed S, Forshaw M, Thomas N, Dinn A. Performance and dependability evaluation of distributed event-based systems: a dynamic code-injection approach. In: ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering. 2017, L'Aquila, Italy: ACM.
- Mohamed S, Forshaw M, Thomas N. Automatic Generation of Distributed Run-time Infrastructure for Internet of Things (IoT). In: International Workshop on Engineering IoT Systems: Architectures, Services, Applications and Platforms. 2017, Gothenburg, Sweden.
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Review
- Schmidt L, Mohamed S, Meader N, Bacardit J, Craig D. Automated data analysis of unstructured grey literature in health research: A mapping review. Research Synthesis Methods 2024, 15(2), 178-197.