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Mathematics and computing is the study and analysis of abstract concepts, such as numbers and patterns. Mathematics is the language of choice for scientifically describing and modelling the universe and everything that happens within it. Computing enables these mathematical problems to be solved in an efficient and automated way.
Efforts to develop an electronic newspaper providing information at the touch of a button took a step forward 50 years ago, and airborne bacteria in the London Underground come under scrutiny, in the weekly dip into Nature’s archive.
Long ties that bridge socially separate regions of networks are critical for the spread of contagions, such as innovations or adoptions of new norms. Contrary to previous thinking, long ties have now been found to accelerate social contagions, even for behaviours that involve the social reinforcement of adoption by network neighbours.
Here, the authors develop a deep-learning algorithm to predict biomarkers from histopathological imaging in advanced urothelial cancer patients. This method detects suitable patients for targeted therapy clinical trials with a significant reduction in molecular testing, providing cost and time savings in real-world clinical settings.
Most research efforts in machine learning focus on performance and are detached from an explanation of the behaviour of the model. We call for going back to basics of machine learning methods, with more focus on the development of a basic understanding grounded in statistical theory.
As quantum technology advances, it holds immense potential to accelerate oncology discovery through enhanced molecular modeling, genomic analysis, medical imaging, and quantum sensing.