Tuberculosis (TB) remains one of the most devastating infectious diseases and its treatment efficiency is majorly influenced by the stage at which the TB germ gets diagnosed. TB represents a public health concern in Malaysia and in many neighbouring countries, with a current incidence annual rate of 80/100,000.
The available methods for TB diagnosis are either time consuming, costly or not efficient. This institutional collaboration is between Anglia Ruskin University and
This project will offer an opportunity to investigate and to develop a mobile enabled Point-of-Care (POC) platform to detect TB.
The total funding for this project is approximately £130,000 which is jointly provided by
AbuHassan, K., Bakhori, N.E.M., Kusnin, N., Azmi, U.Z.M., Tania, M.H., Evans, B., Yusof, N.A., and Hossain, M.A. (2017). Automatic Diagnosis of Tuberculosis Disease Based on Plasmonic ELISA and Color-based Image Classification. 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
Tania, M.H., Lwin, K.T., AbuHassan, K., Bakhori, N.M., MohdAzmi, U.Z., Yusof, N.A. and Hossain, M.A. (2017). An Automated Colourimetric Test by Computational Chromaticity Analysis: A case study of Tuberculosis Test. 11th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB'17), Polytechnic of Porto - Porto (Portugal), 21-23 June, 2017.
Do you have questions, comments or visit our lab? If you would like to chat about the project or if you would like us to visit you to discuss our research, please contact Dr Antesar Shabut.
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