An artificial intelligence programme could be used to more quickly predict the outcome of coronavirus patients by studying X-rays of their chest. Developers at the Oxford-based data-visualisation company, Zegami, have created a machine learning model that can diagnose the virus from the images. However, the team say that in order to get better and more detailed results their AI needs to be trained on a wider range of X-ray images from infected patients. The team believe it could have an artificial intelligence system in place within a matter of weeks to study the disease if it gets enough X-ray images. Zegami CEO, Roger Noble, has written an open letter to the Oxford Health NHS Foundation Trust asking for more images to train the AI model.

Parents letting their child play lots of video games are signing the youngster up for weight gain a decade later, a study has revealed. More than 16,000 children were tracked from age five through to age 14 and scientists assessed the relationship between video games and weight. Results revealed children who regularly played video games as a five-year-old had a higher BMI nine years later, compared to those who did not play video games. Drinking sugary drinks and irregular bedtimes also have a significant impact on children, the study found, and could partly be to blame for the weight change. The study, funded by Cancer Research UK, is the first to look at the potential effect of video game use on children's BMI over time.

Thanks to AHRC Collaborative Doctoral Partnership funding held jointly by Historic Environment Scotland (HES) and the University of Glasgow, we are offering a 45 month (3.75 years) PhD scholarship on developing approaches to integrate automation-led detection routines into workflows used in the professional practice of archaeological prospection and landscape archaeology, notably for large scale heritage management. The supervisors will be Dr Rachel Opitz (Archaeology) and Dr Jan Paul Siebert (Computer Science) at University of Glasgow, and Dr Lukasz Banaszek and Mr David Cowley (HES). Automated detection routines have been viewed as potentially useful or even transformative for several decades, and recent progress in artificial intelligence (AI) based in machine learning and computer vision has moved these approaches from potentially interesting to practically implementable across a variety of applications. Within archaeology, the potential of AI-led approaches and heavily automated image processing for partially automating the identification of archaeological features and landscape changes has been demonstrated in several studies. Their implementation has brought measurable benefits, leading to increased investment in their development. While the technologies themselves are being pursued, less attention has been paid to the analytical and interpretive frameworks within which semi-automated computational approaches to feature identification, notably AIs, are integrated into practices of archaeological landscape interpretation, particularly within heritage management bodies.

Will the critical shortages of therapy radiographers mean that we are about to be replaced by AI, robots and machine learning systems and that will essentially solve the training, retention and employment problems in our profession by stealth? The Society of Radiographers have just announced that the new apprentice programs are now "GO" and where a more vocational training environment in combination with a prospective employer and a degree course will allow employers to "attract and select individuals they believe have the potential to become radiographers". It has also been announced this month that the University of Portsmouth is to close its degree course in radiotherapy and oncology in 2020 for which the timing is particularly ironic and may well impact on recruitment in the South further exacerbating the current problem. I looked at these issues in my January blog and reported on some items in the media relating to this. The College of Radiographers published some of their latest feedback and information on Radiographer Apprenticeships in my February blog and now having read some of the latest books on the impact of Artificial Intelligence on us and especially the workplace, I thought it would be interesting this month to see how this might impact on our profession.

As material handling, automation and maintenance specialists, AMH will not only be providing servicing and maintenance support to all UK customers but it will also be supplying Geek products as part of its warehouse solutions. Geek is a global technology company offering leading intelligent logistics solutions. The advanced robotic and AI solutions can be integrated into automated material handling and logistics systems. The company develops solutions which can automate the process of picking, moving, sorting and retrieving products to improve productivity within warehouses. Utilising Geek robotic technology, AMH is now able to produce flexible and versatile design concepts which allow companies to adapt to the trends of the market place without committing to large investments in fixed automation technology.

The latest research from Cisco says that global internet traffic will reach 4.8 zetabytes a year in 2022, or 150,700 gigabytes a second. That research was published before the current coronavirus pandemic, which may well have a dramatic change in the shape and per-type breakdown of global internet traffic as face-to-face meetings are being overwhelmingly replaced with video conference calls and live video streaming. For example, NAB, the biggest event of the year in media production and distribution, has recently announced it will switch to a virtual conference for the 2020 year, with live presentations and meetings taking place via video streamed over the web. We are all aware of the bandwidth issues and contention that can pose a risk for internet connections. This is particularly true for video transfer over IP because of its need for sustained and consistent data rates and for low-latency packet delivery.

If you do some Google searches for the term "how to invest in artificial intelligence stocks," you'll find a plethora of opinions about what companies you ought to be looking at. Typically, you'll get the "invest in everything with Google" type recommendations which just list some popular tech stocks along with the obligatory NVIDIA (NVDA) mention. Aside from investing in AI chips with NVIDIA, pure-play AI stocks have been far and few between. Now that most companies use machine learning in some way, the definition of an "AI stock" is becoming ever more blurry. As with any disruptive technology, machine learning is changing quickly.

Did you know, that you can transform plain old static ggplot graphs to animated ones? Well you can with the help of the package gganimate by RStudio's Thomas Lin Pedersen and David Robinson and the results are amazing! My STATWORX colleagues and I are very impressed how effortless all kind of geoms are transformed to suuuper smooth animations. That's why in this post I will provide a short overview over some of the wonderful functionalities of gganimate, I hope you'll enjoy them as much as we do! Since Valentine's Day is just around the corner, we're going to explore the Speed Dating Experiment dataset compiled by Columbia Business School professors Ray Fisman and Sheena Iyengar.

An artificial intelligence tool is being developed which researchers hope could be used to predict which coronavirus patients will suffer life-threatening lung damage. The team behind the initial study reported 80% accuracy in its predictions of which patients would develop acute respiratory distress syndrome (ARDS) - which can be fatal in severe COVID-19 cases. The aim of the research is to provide hospitals with a tool to help decide which patients cans safely be sent home and which will need beds and potentially breathing equipment allocated to them. The AI tool used data on 53 patients from two hospitals in China, who all tested positive for coronavirus in January. ARDS is a condition where the lungs, inflamed by serious infection such as pneumonia, cannot provide the body's vital organs with enough oxygen.

Insurance is an industry that thrives on predictability. The more certain the outcome, the more insurance firms can be sure to offer fair rates and generate value for customers and shareholders alike. As such, it's an industry that has been slow to adopt new technologies and adapt to global change. Today, however, change is here, and more is on the way. Global megatrends, from the imminent arrival of the self-driving car to accelerating climate change, threaten to disrupt the insurance sector in a way that's never been seen before.