1. (with A Strub, J Malycha, O Redfern)
    The use of machine learning in clustering ICU patients.
    In preparation (2020)

  2. (with H Khandahari, J Bedford, A Johnson, L. Tarassenko, P. Watkinson)
    Active learning approach to labeling a large ECG set for arrhythmia detection in the ICU
    In preparation (2020)

  3. A Mahdi, P Watkinson, L Tarassenko
    Predicting stroke during hospital re-admission
    In preparation (2020)

  4. A Mahdi, LC Armitage, L Tarassenko, P Watkinson,
    Estimated prevalence of hypertension and undiagnosed hypertension in a large inpatient population: A cross-sectional observational study[Pdf]
    In preparation (2020)

  5. G Qian, A Mahdi
    Sensitivity analysis methods in the biomedical sciences [Pdf]

  6. JW Elting,..., A Mahdi,...,JAHR Claassen
    Assessment of dynamic cerebral autoregulation in humans: Is reproducibility dependent on blood pressure variability? [Pdf]

  7. MAF Pimentel, A Mahdi, O Redfern, MD Santos, L Tarassenko
    Uncertainty-Aware Model for Reliable Prediction of Sepsis in the ICU [Pdf]

  8. A Mahdi, P Watkinson, RJ McManus, L Tarassenko
    Circadian blood pressure variations computed from 1.7 million measurements in an acute hospital setting [Pdf]

  9. LC Armitage, A Mahdi, BK Lawson, C Roman, T Fanshawe, L Tarassenko, AJ Farmer, PJ Watkinson
    Screening for Hypertension in the INpatient Environment (SHINE): a protocol for a prospective study of diagnostic accuracy among adult hospital patients [Pdf]

  10. ML Sanders,..., A Mahdi,...,JAHR Claassen
    Dynamic cerebral autoregulation reproducibility is affected by physiological variability [Pdf]

  11. ML Sanders,..., A Mahdi,...,JWJ Elting
    Reproducibility of dynamic cerebral autoregulation parameters: a multi-centre, multi-method study

  12. D Jarchi, A Mahdi, L Tarassenko and DA Clifton
    Visualisation of long-term ECG signals applied to post-intensive care patients
    2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (2018), 165-168.

  13. D Jarchi, D Salvi, C Velardo, A Mahdi, L Tarassenko and DA Clifton
    Estimation of HRV and SpO2 from wrist-worn commercial sensors for clinical settings
    2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (2018), 144-147

  14. F Andreotti, O Carr, MAF Pimentel, A Mahdi, M De Vos
    Comparing feature-based classifiers and Convolutional Neural Networks to detect arrhythmia from short segments of ECG[Pdf]

  15. A Mahdi, D Nikolic, AA Birch, SJ Payne
    At what data length do cerebral autoregulation measures stabilize? [Pdf]

  16. A Mahdi, E Rutter, SJ Payne
    Effects of non-physiological blood pressure artefacts on cerebral autoregulation [Pdf]

  17. A Mahdi, A Ferragut, C Valls, C Wiuf
    Conservation laws in chemical reaction networks [Pdf]

  18. A Mahdi, D Nikolic, AA Birch MS Olufsen, DM Simpson, R Panerai, SJ Payne
    Increased blood pressure variability upon standing up improves reproducibility of cerebral autoregulation indices [Pdf]

  19. A Mahdi, GD Clifford, SJ Payne
    A model for generating synthetic blood pressure waveform [Pdf]

  20. PE Jacob, SMM Alavi, A Mahdi, SJ. Payne, D Howey
    Bayesian inference in non-Markovian state-space models with applications to fractional order systems [Pdf]

  21. A Mahdi, C Pessoa, J Hauenstein
    A hybrid symbolic-numerical appraoch to the center-focus problem [Pdf]

  22. SMM Alavi, A Mahdi, SJ Payne, D Howey
    Identifiability of Generalized Randles Circuit Models[Pdf]

  23. G Mader, MS Olufsen, A Mahdi
    Modeling cerebral blood flow velocity during orthostatic stress [Pdf]

  24. A Mahdi, N Meshkat, S Sullivant
    Structural identifiability of viscoelastic mechanical systems [Pdf]

  25. J Harlim, A Mahdi, A Majda
    An Ensemble Kalman Filter for Statistical Estimation of Physics Constrained Nonlinear Regression Models [Pdf]

  26. A Mahdi, JT Ottesen, J Sturdy, MS Olufsen
    Modeling the afferent dynamics of the baroreflex control system [Pdf]