Harnessing AI in the fight against COVID-19
04 June 2020AI assisted COVID-19 diagnostic and prognostic tool could improve resource allocation and patient outcomes.
AI assisted COVID-19 diagnostic and prognostic tool could improve resource allocation and patient outcomes.
Six affiliates of the ̽»¨Ö±²¥ of Cambridge are among 50 world-leading UK researchers who have been elected to the prestigious Fellowship of the Academy of Medical Sciences.
Seven of Europe’s leading cancer centres have today published a report detailing how they have organized their healthcare systems at an unprecedented scale and pace to make their operations ‘pandemic proof’ during the COVID-19 pandemic.
Dr Karen Pinilla is a clinical research fellow at the Cancer Research UK Cambridge Centre. She worked as a clinician in the breast unit at Addenbrooke’s Hospital before starting her fellowship in October 2019. She is now based in both Addenbrooke’s Hospital and the Cancer Research UK Cambridge Institute.
Scientists have created one of the most detailed maps of breast cancer ever achieved, revealing how genetic changes shape the physical tumour landscape, according to research funded published in .
A new type of scan that involves magnetising molecules allows doctors to see in real-time which regions of a breast tumour are active, according to research at the ̽»¨Ö±²¥ of Cambridge and published in Proceedings of the National Academy of Sciences.
Scientists at AstraZeneca, a global biopharmaceutical company, have been working with Cambridge ̽»¨Ö±²¥Â for more than two decades. What are the secrets of their success?
Cambridge scientists are set to benefit from a major cash injection from Cancer Research UK and partners to develop radical new strategies and technologies to detect cancer at its earliest stage.
Researchers from the Cambridge Biomedical Campus have featured prominently in this year’s election to the prestigious European Molecular Biology Organisation (EMBO).
̽»¨Ö±²¥genetic and molecular make-up of individual breast tumours holds clues to how a woman’s disease could progress, including the likelihood of it coming back after treatment, and in what time frame, according to a published in Nature.