Cambridge Centre for AI in Medicine
World-leading machine learning (ML) technology developed at the University of Cambridge promises powerful new prediction and analytical tools to support the clinical care of individuals with the life-limiting condition. The work is being presented at the North American Cystic Fibrosis Conference 2020, running online from 7 to 23 October. The three research projects highlighted below […]
Paper on COVID-19 hospital capacity planning accepted by Machine Learning
A paper authored by Zhaozhi Qian, Ahmed Alaa, and CCAIM Director, Professor Mihaela van der Schaar has been accepted for publication in Machine Learning (editor-in-chief: Hendrik Blockeel). The paper, entitled “CPAS: the UK’s National Machine Learning-based Hospital Capacity Planning System for COVID-19,” was accepted for publication on September 24. The authors introduce a capacity planning […]
How pioneering Machine Learning can help to future-proof clinical trials in the era of COVID-19
The coronavirus pandemic is the greatest global healthcare crisis of our generation, presenting enormous challenges to medical research, including clinical trials. Advances in Machine Learning are providing an opportunity to rapidly adapt clinical trials and lay the groundwork for smarter, faster and more flexible clinical trials in the future. In an article published in Statistics […]
AI standards launched to help tackle problem of overhyped studies
The first international standards for the design and reporting of clinical trials involving artificial intelligence have been announced in a move experts hope will tackle the issue of overhyped studies and prevent harm to patients, The Guardian reports. “These new reporting guidelines […] are a partial but valuable solution that could help catalyse a top-to-bottom […]
Synthetic data: breaking the data logjam in machine learning for healthcare
“Machine learning has the potential to catalyze a complete transformation in healthcare, but researchers in our field are still hamstrung by a lack of access to high-quality data, which is the result of perfectly valid concerns regarding privacy,” says CCAIM Director, Professor Mihaela van der Schaar. “It’s a huge problem that demands a big, creative […]
AutoML: powering the new human-machine learning ecosystem
The van der Schaar lab, led by CCAIM’s Director, Professor Mihaela van der Schaar, has published a major new thought piece on automated machine learning (AutoML). AutoML will be the key to revolutionising healthcare and delivering truly personalised precision medicine. The team has distilled years of extensive research on to single web page, and also […]
Vacancy: Artificial Intelligence and Machine Learning Team Leader
CCAIM team member Dr Sarah Teichmann is Head of Cellular Genetics and a Senior Group Leader at the Sanger Wellcome Institute. An exciting opportunity has arisen for an Artificial Intelligence/Machine Learning (AI/ML) specialist to join the institute’s Cellular Genetics Programme team. Find out more about the vacancy.
Andres Floto features in the Science, Policy & Pandemics podcast
This week, CCAIM Co-Director, Professor Andres Floto features in the Science, Policy and Pandemics podcast, a panel-based discussion programme produced by the University of Cambridge Centre for Science and Policy and hosted by Dr Robert Doubleday. Professor Floto discusses the scientific and medical responses to the COVID-19 pandemic, and the technology that could help to […]
Mihaela van der Schaar at ICML 2020
The lab led by the Director of the Cambridge Centre for AI in Medicine, Professor Mihaela van der Schaar, has had 7 papers accepted for ICML 2020, which kicks off this week. Professor van der Schaar is a listed author on all papers, which puts her among the top 10 authors at ICML this year […]
Mihaela van der Schaar to give tutorial at MLSS 2020
CCAIM Director, Mihaela van der Schaar, will deliver a tutorial at the 2020 Machine Learning Summer School to be hosted by the Max Planck Institute for Intelligent Systems from June 28 through July 10. Mihaela will present her tutorial, entitled “Machine Learning for Healthcare” on July 8 and July 9. In her talk, she will explore the […]
