BioSymetrics’ VP of Data Science Research, Victoria Catterson, describes the company’s collaboration with Humanigen and work more broadly in COVID-19.

This is the first installment in a series that will explain various ways that the quality of a binary classification model can be summarized as metrics. Before such metrics can be discussed the output from these models must be understood and organized.

Feature selection results in an information-rich vector of understandable features, ultimately leading to higher performing and more explainable models. The correct approach is to consider features in combination, in order to maximize the information available to the model.

Weighting patients according to demographic profile, allows for clearer comparison of potential risk factors, ultimately revealing true correlations between sub-groups and mortality rate/outcomes.

Our recent work where we used Contingent AI™ to differentiate ARDS patients from other patients requiring mechanical ventilation in the ICU is now available for all to read at MedRxiv.

Guest Blog Post: Jenyse Ramage, Operations Manager and Product Lead at BioSymetrics discusses time management, behaviour, and Homeostatic Response.

We are proud to announce that our own Gabe Musso, Chief Science Officer, will be delivering the key note at Hub Xchange's AI in Drug Discovery event on Wednesday, December 2, 2020