We aim to develop automated workflows for analysis of blood films.
We are examining how Full Blood Count tests can be used to identify patients with heart and brain diseases earlier.
We are investigating how Full Blood Count data can be used to improve the diagnosis of blood disorders.
We are implementing a test for iron deficiency using the Full Blood Count.
We are developing sophisticated machine learning models for use with Full Blood Count data.
Can our algorithms be applied to other infectious diseases, such as malaria?
Can we use our detection systems to identify new, unknown pandemics?
We are exploring whether we can use Full Blood Count data to identify women at risk of serious complications during pregnancy.
Can Full Blood Count data be used to identify individuals at high risk of renal cell carcinoma?
We have developed machine learning models which can detect the SARS-CoV-2 outbreak in Cambridge.