• We combine statistics for its robustness with machine learning for its management of complexity.
• We uncompromisingly choose for robustness to ensure the long term success of the projects.
• We estimate clinical and business risks at all stages of the processes.
• We resolutely tackle methodological bottlenecks that hinder advancement of the diagnostics field.
• We evolve statistical methods to match the dynamics of clinical data and clinicians' expert knowledge.
• We continuously invest in the development of adapted IT and software architecture.
• We aim to pave a way towards personalised medicine by developing intermediate solutions.