A new section for Volv, we hope you find these blogs interesting

Nigh Sky sml12 Jan 2021
Why can’t we find the 50% of people with rare diseases?Christopher Rudolf

It might be said that picking out patterns to identify patients with rare diseases is a bit like distinguishing thousands of constellations of stars. Neither is within the scope of the human eye and both require extremely advanced technologies to even begin to decipher and separate patterns. Yet finding the 50 percent of undiagnosed patients with one of the approximately 7,000 rare diseases is a medical and clinical imperative.

Img Interp Models Draw17 Apr 2020
From predictive to interpretable modelsChristopher Rudolf

When we work on complex prediction models with our inTrigue methodology, we are often asked to help clinicians and others to interpret these models by listing the patient features (attributes) which are used by the model to form its predictions. And indeed, generating a list of predictors ranked by their ‘importance’ in a model can translate to improved interpretability and clinical impact. However, there is some work that needs to be carefully considered in order to produce tooling that is derived from complex models that can provide real benefit in a clinical situation.

Volv Seedlink2000x10002 Feb 2018
Finding Patients for Rare Diseases: Accurate insight into rare diseases enhanced by AIChristopher Rudolf

This case study derives from an ongoing Volv engagement, which started in July 2017. A pharmaceutical company approached Volv Global to develop a prediction model to identify additional patients suffering from the rare disease treatable by its specialist medicine.