Tuberculosis Disease Diagnosis Using AI, Bio-sensor and Digital Technology

2 May 2018, 12:00 - 14:00
Chelmsford campus

Join Dr Antesar Shabut as she discusses the results of our recent TB-Test project. The presentation followed by a Q&A session will take place 12:00 - 13:00. Lunch and networking will take place 13:00 - 14:00.


Tuberculosis (TB) remains one of the most devastating infectious diseases and is one of the top 10 causes of death worldwide. In 2016, 10.4 million people worldwide fell ill with TB, and 1.7 million died from the disease. Over 95% of TB deaths occur in low- and middle-income countries.

Early and accurate diagnosis is key to the spread of this treatable and curable disease. The TB-Test project aims to develop a simple, accurate, and cost effective TB testing in order to help achieve global tuberculosis control. A TB-Test app is introduced which works as a point of care that offers a low cost, and user friendly mobile-based application that will deliver TB testing anywhere in the world, 24/7 in real time.

In this seminar, the results of the TB-Test project are demonstrated. The research behind implementing an efficient image-processing platform is also presented. Images are extracted from a plasmonic ELISA for TB antigen-specific antibodies and their features analysed. Both unsupervised and supervised machine learning techniques are utilised to extract samples and classify those samples into positive and negative based on eighteen colour histogram features. The proposed system is trained off-line, followed by testing and validation using a separate set of images in real-time. Using an ensemble classifier, Random Forest, we demonstrated 98.4% accuracy in TB antigen-specific antibody detection on the mobile platform. Our mobile application has the capabilities to provide prediction in real time without any attachment or virtual plate which demonstrated its validity to aid efforts in eradicating the TB disease.


Dr Antesar Shabut is a Research Fellow within the Anglia Ruskin IT Research Institute. Dr Antesar received her PhD degree from the University of Bradford, United Kingdom, in July 2015, which involved modelling computational trustworthiness evaluation techniques and recommender systems for mobile ad hoc environments. She received the MSc degree from Sheffield Hallam University, United Kingdom, in November 2008 in IT Consultancy. Prior to joining the Anglia Ruskin University, she was a research assistant at the University of West of Scotland and she also worked as a teaching and research assistant at the University of Bradford during her PhD study.

Dr Shabut’s current research interests lie in the areas of applied AI to mobile based intelligent systems, image processing, computer vision, and trust and cyber security modelling in distributed systems. She has published several papers in reputed journals and conferences.

Event Details

2 May 2018, 12:00 - 14:00
Chelmsford campus
Free to attend - lunch is provided

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