Organ Transplantation
The latest breakthroughs from our team of researchers and partnered organisations.
External Validity of Machine Learning-based Prognostic Scores for Cystic Fibrosis – new publication
A paper recently accepted for publication by PLOS Digital Health explores machine-learning based prognostic scores and their validity when applied to demographically different patient cohorts: the ‘external validity’. The publication is the latest accomplishment in CCAIM’s ongoing efforts to push forward in cystic fibrosis research with the Floto lab and van der Schaar lab on…
Alexander Gimson – ML in Transplantation Medicine
Dr Alexander Gimson, member of the CCAIM faculty, talks about the impact of machine learning on transplantation medicine.
Continue Reading Alexander Gimson – ML in Transplantation Medicine
Cutting-Edge Clinicians: Machine learning will make organ allocation more equitable in the UK
Dr. Alexander Gimson is leading Britain’s national team dedicated to improving the country’s existing organ allocation scheme to save more lives. Dr. Gimson and colleagues at the van der Schaar Lab and Cambridge Centre for AI in Medicine (CCAIM) are advocating for OrganITE – a novel machine learning solution whereby organs are offered to patients…
OrganITE: A pioneering ML system that helps clinicians make the most of scarce organs by predicting suitability for each patient
The van der Schaar Lab has developed a machine learning solution that goes beyond the scope of contemporary organ-to-patient matching policies by also accounting for the rarity of organs available for transplantation. Organ transplantation is an incredibly high stakes, life-and-death clinical practice. Making the decision to give an organ to one patient over another involves…
