Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Computer science is the study and development of the protocols required for automated processing and manipulation of data. This includes, for example, creating algorithms for efficiently searching large volumes of information or encrypting data so that it can be stored and transmitted securely.
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.
An article in IEEE Journal on Selected Areas in Communications proposes algorithmic solutions to dynamically optimize MIMO waveforms to minimize or eliminate interference in autonomous machine-to-machine communications.