COVID-19 Collaboration

Elevator Pitch - Incorporation bias in medical machine learning models

Spotlight on Incorporation Bias. Mr. Derek Driggs highlights a finding from our systematic review, which is also systemic in the machine learning literature. Incorporation bias is introduced when the outcome labels are not independent of the predictors. Find out more at the link right.

Lessons from the pandemic for machine learning and medical imaging

Dr Michael Roberts presented our latest update on the key lessons from this pandemic and how we can be more prepared for next time.

Our collaboration is also featured in SIAM News. Providing an overview of the particular imaging challenges for machine learning during a pandemic and lessons that have been learned.

Artificial intelligence has been of little use for diagnosing COVID-19

We are featured in the New Scientist! In the wake of our systematic review, Michael Roberts penned an opinion piece discussing the complexities of applying machine learning to a pandemic and some fundamental issues for applying machine learning in healthcare.

Pandemic machine learning pitfalls

Derek Driggs, of our collaboration, appeared on the Data Skeptic Podcast and discussed in detail the issues with existing machine learning models for COVID-19 prognosis and diagnosis along with how these could be improved.

Artificial intelligence Covid breakthrough will save lives

Press release from Cambridge University Hospitals (CUH) about AIX-COVNET. Our collaboration is discussed in a press release from CUH describing how our algorithms will save the lives of patients.

AI at the forefront of efforts to treat coronavirus patients

Media reporting of AIX-COVNET. Our collaboration was recently featured in several government and NHSX press releases and featured in several news articles.

AIX-COVNET

Our group is helping to lead an international collaboration of researchers to develop AI models for the diagnosis and prognostication of COVID-19 from CT and X-ray images. Currently, the diagnosis of COVID-19 is most often confirmed by a laboratory test (RT-PCR), however, the test has high false-negative rates leading to delayed diagnosis, treatment, and quarantine.

Cambridge Image Analysis