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Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms. (2023)
Presentation / Conference Contribution
FOUGH, F., JANJUA, G., ZHAO, Y. and DON, A.W. 2023. Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea (MetroSea 2023); learning to measure sea health parameters, 4-6 October 2023, La Valletta, Malta. Piscataway: IEEE [online], pages 121-126. Available from: https://doi.org/10.1109/MetroSea58055.2023.10317294

Antimicrobial resistance (AMR) is an increasingly critical public health issue necessitating precise and efficient methodologies to achieve prompt results. The accurate and early detection of AMR is crucial, as its absence can pose life-threatening r... Read More about Predicting and identifying antimicrobial resistance in the marine environment using AI and machine learning algorithms..

Influence of the training set composition on the estimation performance of linear ECG-lead transformations. (2023)
Presentation / Conference Contribution
GULDENRING, D., FINLAY, D.D., BOND, R.R., KENNEDY, A., DOGGART, P., JANJUA, G. and MCLAUGHLIN, J. 2023. Influence of the training set composition on the estimation performance of linear ECG-lead transformations. In Proceedings of the 50th Computing in cardiology 2023 (CinC 2023), 1-4 October 2023, Atlanta, GA, USA. Piscataway: IEEE/CinC [online], 50, article number 263. Available from: https://doi.org/10.22489/CinC.2023.263

Linear ECG-lead transformations (LELTs) are used to estimate unrecorded target leads by applying a number of recorded basis leads to a LELT matrix. Such LELT matrices are commonly developed using training datasets that are composed of ECGs that belon... Read More about Influence of the training set composition on the estimation performance of linear ECG-lead transformations..

Evaluation of pulse transit time for different sensing methodologies of arterial waveforms. (2023)
Journal Article
JANJUA, G.M.W., FINLAY, D., GULDENRING, D., HAQ, A.U. and MCLAUGHLIN, J. 2023. Evaluation of pulse transit time for different sensing methodologies of arterial waveforms. IEEE access [online], 11, pages 33928-33933. Available from: https://doi.org/10.1109/ACCESS.2023.3264291

We perform a novel comparative analysis between optically and mechanically derived pulse transit time (PTT), which is a universally employed technique for cuffless blood pressure (BP) estimation. Two inline photoplethysmogram (PPG) sensors were place... Read More about Evaluation of pulse transit time for different sensing methodologies of arterial waveforms..