Precision Analytics for Medicine
Next generation analysis for next generation data
Modern medicine presents us with data of unprecedented complexity and dimensionality. Yet most mathematical and statistical tools used routinely to analyse such data date from the 1970s. There is a clear and unmet need for innovation. Realising truly personalised data-driven precision medicine requires more advanced mathematical methodology.
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2019/10: publication of the study `Analysis of overfitting in the regularized Cox model' (Journal of Physics A)
2019/09: initiation of formal collaboration on breast cancer data analytics, with King's College London and Owkin Paris
(grant application submitted to Innovate UK and CRUK)
2019/03: publication of the study `Accurate Bayesian data classification without hyperparameter cross-validation'
(Journal of Classification)
2018/11: The SaddlePoint Signature analytics pipeline is installed at Erasmus Medical Center Rotterdam (Dept of Epidemiology).
2018/08: publication of the study `Heterogeneity in risk of prostate cancer: A Swedish population-based cohort study of competing risks and Type 2 diabetes mellitus', based on application of the SaddlePoint Mosaic software (International Journal of Cancer).
2018/07: the EU consortium RGS@home, in which SaddlePoint Science is the analytics partner, has been awarded an EIT Health grant (ranked 2nd out of 175 applications). RGS@home will start early 2019.