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Read more at: Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case

Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case

25 September 2023

Artificial intelligence (AI) methods applied to healthcare problems have shown enormous potential to alleviate the burden of health services worldwide and to improve the accuracy and reproducibility of predictions. In particular, developments in computer vision are creating a paradigm shift in the analysis of radiological...

Read more at: Career intentions of medical students in the UK: a national, cross-sectional study (AIMS study)

Career intentions of medical students in the UK: a national, cross-sectional study (AIMS study)

15 September 2023

CMIH Hub investigator Prof. Richard Samworth and his AIMS study colleagues recently published the largest survey of it's kind exploring the career intentions of UK medical students within two years of graduating. The survey found that almost a third of the respondants intended to change career or leave the UK to practice...

Read more at: Navigating the development challenges in creating complex data systems

Navigating the development challenges in creating complex data systems

1 June 2023

Machine learning is in a reproducibility crisis. Many codebases simply do not run when tested outside of the development environment and, even when they do run, many algorithms do not generalise outside of the dataset on which they are trained. In this paper, researchers from the CMIH Hub and AIX-CO VNET teams argue that...

Read more at: Multi-modal learning for predicting the genotype of glioma

Multi-modal learning for predicting the genotype of glioma

22 May 2023

Glioma is the most common malignant brain tumour in adults. These tumours often vary between people resulting in very different outcomes.One of the most significant markers for the diagnosis and prognonsis of glioma is a mutation of the isocitrate dehydogenase (IDH) gene. Studies have shown that MRI can predict the...

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The Cambridge Mathematics of Information in Healthcare Hub (CMIH) is a collaboration between mathematics, statistics, computer science and medicine, aiming to develop robust and clinically practical data analytics algorithms for healthcare decision making. Our work focusses on some of the most challenging public health problems; Cancer, Cardiovascular Disease, and Dementia.

 

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cmih@maths.cam.ac.uk

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