Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Items where Author is "Keenan, R"

Up a level
Export as [feed] Atom [feed] RSS
Group by: Item Type | No Grouping
Number of items: 5.

Khalaf, M, Hussain, A, Keight, R, Al-Jumeily, D, Fergus, P, Keenan, R and Tso, P (2017) Machine Learning approaches to the application of Disease Modifying Therapy for Sickle Cell using Classification Models. NEUROCOMPUTING, 228. pp. 154-164. ISSN 0925-2312

Khalaf, M, Hussain, A, Al-Jumeily, D, Keight, R, Keenan, R, Fergus, P, AlAskar, H, Shaw, A and Olatunji, I (2016) Training Neural networks for Experimental models: Classifying Biomedical Datasets for Sickle Cell Disease. In: Intelligent Computing Theories and Application: Lecture Notes in Computer Science , 9771. pp. 784-795. (2016 International Conference on Intelligent Computation, 02 August 2016 - 05 August 2016, Lanzhou,China).

Edwin, C, Dean, J, Bonnett, L, Phillips, KLE and Keenan, R (2016) Non-tumour bone marrow lymphocytes correlate with improved overall survival in childhood acute lymphoblastic leukaemia. Pediatric Blood and Cancer, 63 (10). pp. 1848-1851. ISSN 1545-5009

Khalaf, M, Hussain, A, Keight, R, Al-Jumeily, D, Keenan, R, Fergus, P and Idowu, IO (2016) The Utilisiation of composite Machine Learning models for the Classification of Medical Datasets For Sickle Cell Disease. In: 2016 Sixth International Conference on Digital Information Processing and Communications (ICDIPC) . (Sixth International Conference on Digital Information Processing and Communications (ICDIPC), 21 April 2016 - 23 April 2016, Lebanon).

Khalaf, M, Hussain, A, Al-Jumeily, D, Fergus, P, Keenan, R and Radi, N (2015) A Framework to Support Ubiquitous Healthcare Monitoring and Diagnostic for Sickle Cell Disease. In: Intelligent Computing Theories and Methodologies: Lecture Notes in Computer Science , 9226. (International Conference on Intelligent Computation, 20 August 2015 - 23 April 2016, Fuzhou, China).

This list was generated on Thu Apr 18 04:52:29 2024 UTC.