Azzam F G Taktak
Affiliation: University of Liverpool
- A web-based tool for the assessment of discrimination and calibration properties of prognostic modelsAzzam F G Taktak
Department of Clinical Engineering, Royal Liverpool University Hospital, 1st Floor, Duncan Building, Daulby Street, Liverpool L7 8XP, UK
Comput Biol Med 38:785-91. 2008..We conclude that prognostic models should be assessed both in terms of discrimination and calibration and that calibration analysis should be carried out numerically and graphically...
- Double-blind evaluation and benchmarking of survival models in a multi-centre studyA Taktak
Department of Clinical Engineering, Royal Liverpool University Hospital, Liverpool, UK
Comput Biol Med 37:1108-20. 2007..It was concluded that powerful, recent flexible modelling algorithms show a comparative predictive performance to that of more established methods from the medical and biological literature, for the reference data set...
- Estimating prognosis for survival after treatment of choroidal melanomaBertil Damato
Ocular Oncology Service, Royal Liverpool University Hospital, Prescot St, Liverpool L7 8XP, UK
Prog Retin Eye Res 30:285-95. 2011....
- Genetic heterogeneity in uveal melanoma assessed by multiplex ligation-dependent probe amplificationJustyna Dopierala
Department of Pathology, School of Cancer Studies, University of Liverpool, Liverpool, UK
Invest Ophthalmol Vis Sci 51:4898-905. 2010..To determine intratumor genetic heterogeneity in uveal melanoma (UM) by multiplex ligation-dependent probe amplification (MLPA) in formalin-fixed, paraffin-embedded (FFPE) tumor tissues...
- Whole-genome microarray detects deletions and loss of heterozygosity of chromosome 3 occurring exclusively in metastasizing uveal melanomaSarah L Lake
Pathology Department, School of Cancer Studies, University of Liverpool, Liverpool, UK
Invest Ophthalmol Vis Sci 51:4884-91. 2010..To detect deletions and loss of heterozygosity of chromosome 3 in a rare subset of fatal, disomy 3 uveal melanoma (UM), undetectable by fluorescence in situ hybridization (FISH)...
- Artificial neural networks estimating survival probability after treatment of choroidal melanomaBertil Damato
Ocular Oncology Service, Royal Liverpool University Hospital, Liverpool, United Kingdom
Ophthalmology 115:1598-607. 2008..e., any uveal melanoma involving choroid) and to demonstrate the value of entering age, sex, clinical stage, cytogenetic type, and histologic grade into the predictive model...
- Automated post hoc removal of power-line and CRT frame pulse contamination from retinal and cortical evoked potentials (EPs)Anthony C Fisher
Department of Clinical Engineering and Clinical Eye Research Centre, Royal Liverpool University Hospital, Medical School, Duncan Building, Liverpool, L7 8XP, UK
Doc Ophthalmol 112:169-75. 2006..Here the simple theory is illustrated in artificial datasets and then applied to clinical examples of PERG and VEP. The programming language used throughout is MatLab R13SP3 (Mathworks UK Ltd.)...
- On the use of multi-objective evolutionary algorithms for survival analysisChristian Setzkorn
Royal Liverpool University Hospital, Liverpool, United Kingdom
Biosystems 87:31-48. 2007..The approach is evaluated on several artificial datasets and one medical dataset. It is shown that the approach is capable of producing accurate models, even for problems that violate some of the assumptions made by classical approaches...
- Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theoremAzzam F G Taktak
Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP, UK
Phys Med Biol 49:87-98. 2004..We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate...
- The use of artificial neural networks in decision support in cancer: a systematic reviewPaulo J Lisboa
School of Computing and Mathematical Science, Liverpool John Moores University, Liverpool, UK
Neural Netw 19:408-15. 2006..This paper reviews the clinical fields where neural network methods figure most prominently, the main algorithms featured, methodologies for model selection and the need for rigorous evaluation of results...