The application of high-performance computing could have far-reaching implications for bioinformatics and life sciences researchers, as Robert Roe discovers
Developments in bioinformatics are putting pressure on those tasked with data analysis and interpretation, writes Sophia Ktori
In January 2020 the American Diabetes Association released a new set of clinical standards that, for the first time, included the use of an FDA-approved autonomous artificial intelligence (AI) platform for detecting diabetic retinopathy in people with diabetes.
At the end of February physIQ and the US Department of Veteran’s Affairs published data from a clinical trial demonstrating the use of physIQ’s machine-learning algorithm to predict when an individual patient with previously diagnosed heart failure will likely require a readmission to hospital.
Cloud research tools provide a platform for new avenues of scientific research by providing fast access to bare-metal resources.
New processors and GPU technology continue to demand more power than the previous generations, combining this with increasingly dense architectures requires cooling solutions such as liquid or immersion cooling.
Tate Cantrell, CTO, Verne Global, comments on the cost of the AI computing revolution
European researchers are working on a new programming environment for exascale computing that aims to make using these systems more efficient and programmers more productive.
