Chronic Kidney Disease and Acute Kidney Injury (MRC CKD project)

  • S. Tirunagari, S.C. Bull and N. Poh, Automatic Classification of Irregularly Sampled Time Series with Unequal Lengths: A Case Study on Estimated Glomerular Filtration Rate, IEEE International Workshop on Machine Learning for Signal Processing, Sept. 13—16, 2016, Salerno, Italy, 2016. [pdf]
  • S. Tirunagari, S. C. Bull and N. Poh, Automatic Detection of Acute Kidney Injury Episodes from Primary Care Data, IEEE SSCI CICARE, accepted, Greece, 2016. [pdf]
  • N. Poh, A. McGovern, and S. de Lusignan. Improving the measurement of longitudinal change in renal function: automated detection of changes in laboratory creatinine assay. Journal of Innovation in Health Informatics, 22(2), 293-301. [Publisher's link] [Technical report in pdf]
  • N. Poh and S. de Lusignan, Calibrating Longitudinal eGFR in Patience Records Stored in Clinical Practices Using a Mixture of Linear Regressions, Workshop on Pattern Recognition for Healthcare Analytics, ICPR 2012, Tsukuba Science City, Japan, 2012. [pdf]
  • N. Poh and S. de Lusignan, Modeling Rate of Change in Renal Function for Individual Patients: A Longitudinal Model Based on Routinely Collected Data, Neural Information Processing Systems (NIPS) Personalized Medicine Workshop 2011 (NIPS PM 2011), Sierra Nevada. [pdf] [Download the likelihood table] [spotlight presentation]

Healthcare analytics

  • S. Tirunagari, S.C. Bull, S. Kouchaki, D. Cooke and N. Poh, Visualisation of Survey Responses using Self-Organising Maps: A Case Study on Diabetes Self-care Factors, SSCI CICARE, accepted, Greece, 2016 [pdf]
  • S. Tirunagari, N. Poh, H. Abdulrahman, N.  Nemmour, and D. Windridge, Breast Cancer Data Analytics With Missing Values: A study on Ethnic, Age and Income Groups, Dept of Computing Technical Report, TR-15-01, 2015. [link]
  • S. Tirunagari, N. Poh, K. Aliabadi, D. Windridge, and D. Cooke, Patient Level Analytics Using Self-Organising Maps: A Case Study on Type-1 Diabetes Self-care Survey Responses, IEEE Symposium on Computational Intelligence and Data Mining, Orlando, pp.304,309, 2014. [pdf]
  • N. Poh and S. de Lusignan, Data-modelling and visualisation in chronic kidney disease (CKD): a step towards personalized medicine, Informatics in Primary Care, 19(2) [pdf]

Healthcare platform

  • N. Poh, S. Tirunagari and D. Windridge, Challenges in Designing an Online Healthcare Platform for Personalised Patient Analytics, IEEE Symposium on Computational Intelligence in Big Data, Orlando, pp. 1-6, 2014. [pdf]
  • N. Poh and A. Katibi, Addressing Privacy Concerns in Secondary Use of Centralized Clinical Medical Records through Data Protection, System Architecture Design, and Vulnerability Assessment, Dept of Computing Technical Report, TR-14-02, 2014. [pdf]
  • H. Abdulrahman, N. Poh and J. Burnett, Privacy Preservation, Sharing and Collection of Patient Records using Cryptographic Techniques for Cross-Clinical Secondary Analytics, IEEE Symposium on Computational Intelligence in healthcare and e-health, Orlando, pp. 148-153, 2014. [pdf]
  • Simon de Lusignan, Josephine Cashman, Norman Poh, Georgios Michalakidis, Aaron Mason, Terry Desombre, Paul Kraus, Conducting Requirements Analyses for Research using Routinely Collected Health Data: a Model Driven Approach, Studies in Health Technology and Informatics, Volume 180, pg 1105-1107, 2012 [link]

Learning analytics

  • N. Poh and I. Smythe, To What Extend Can We Predict Students' Performance? A Case Study in Colleges in South Africa, IEEE Symposium on Computational Intelligence and Data Mining, Orlando, accepted, Orlando, 2014. [pdf]