It’s here – the Smart Health issue of @CS4FN magazine, coming to a school near you soon, or grab a free PDF online ^JB

Our long-awaited (Covid-delayed) 27th issue of the CS4FN magazine, on Smart Health, is here and enough copies (plus some spares) are currently being printed so that ~21,000 copies can be posted to our 2,430 UK subscribing schools. While we can only post printed copies to UK schools the PDF version is freely available to anyone, along with our entire back catalogue.

If you’d like to sign your school up to receive copies of our future magazines please sign up using the purple form here.

FREE PDFs of the magazine available here.

Download a PDF copy of CS4FN issue 27 – Smart Health

The Smart Health issue of the magazine looks at the work of the EPSRC-funded Pambayesian project at Queen Mary University of London, which is about “Patient Managed Decision-Support using Bayesian Networks”, or using technology to help patients and doctors make decisions about treatments.

“The trouble with healthcare is that it’s becoming ever more expensive: new drugs, new treatments, more patients, the ever-increasing time needed with experts. We want everyone to get the care they need, but the costs are growing. Perhaps computer scientists can help? Research groups worldwide are exploring ways to create intelligent programs that can support patients at home, helping monitor them and make decisions about what to do.

For example, say you are on powerful drugs to manage a long term illness: should you have the vaccine? Can you have a baby? Is a flare up of your disease about to hit you and how can you avoid it? Is the new ache a side effect of the drugs? Do you need to change medicines? Do you need to see a specialist? If artificial intelligences can help support patients then the doctors and nurses can spend more time with those who need it, hospitals can save on expensive drugs that aren’t working, and patients can have better lives. But what kind of technology can deliver this sort of service? In this issue, we explore one particular way being developed on the EPSRC funded PAMBAYESIAN project at Queen Mary University of London, based on an area of computing called Bayesian networks, that might just be the answer.”


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