Abstract:
This paper performs an investigation into the development of an intelligent image-based automatic in vitro diagnostic system for infectious diseases using personal device...Show MoreMetadata
Abstract:
This paper performs an investigation into the development of an intelligent image-based automatic in vitro diagnostic system for infectious diseases using personal devices. The proposed framework of the image-based diagnostic system is demonstrated using the case study of Tuberculosis (TB)-specific antibody detection. The developed system, denoted as the iTB-test, is an intelligent bio-sensing system, comprised of a plasmonic Enzyme-Linked Immunosorbent Assay based colourimetric test in combination with an artificial intelligence-enabled image-based system. The presented system can separate the region of interest with 99.62% accuracy using clustering-based hybrid image processing algorithms, whereas the classification accuracy of antibody detection using a supervised machine learning technique is 100% based on the experiments conducted for the case study.
Published in: 2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
Date of Conference: 02-04 December 2022
Date Added to IEEE Xplore: 06 February 2023
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Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
Institute of Information Technology Jahangirnagar University, Savar, Bangladesh
Faculty of Business, Computing and Digital Industries Leeds Trinity University, Leeds, UK
School of Computing and Engineering University of West London, London, UK
Department of Computer Science, Nottingham Trent University, Nottingham, UK
Cambodia University of Technology and Science, Penh, Cambodia
Contents Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
Institute of Information Technology Jahangirnagar University, Savar, Bangladesh
Faculty of Business, Computing and Digital Industries Leeds Trinity University, Leeds, UK
School of Computing and Engineering University of West London, London, UK
Department of Computer Science, Nottingham Trent University, Nottingham, UK
Cambodia University of Technology and Science, Penh, Cambodia
