Data Science Insider: September 24th, 2021

In This Week’s SuperDataScience Newsletter: Scientists Use AI to Create Drug Regime for Rare Form of Brain Cancer in Children. Greece Used ML Algorithm to Target Covid Testing of Travellers. The Biggest AI Trends for 2022. UK Publishes 10-year Plan to Become ‘AI Superpower’. UK Court of Appeal Rejects AI Inventor Claims. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [AI Creates Drug Regime to Treat Brain Cancer in Children]( brief: Scientists have used AI to create a drug regime for children with a type of deadly brain cancer, where survival rates have not improved for 50 years. Diffuse intrinsic pontine glioma (DIPG) is a rare and fast-growing type of brain tumour in children. These types of tumours are difficult to remove surgically because they are diffuse, which means they do not have well-defined borders suitable for operations. A quarter of children with DIPG have a mutation in a gene known as ACVR1, but there are currently no treatments approved to target this mutation. In a new study, scientists at the Institute of Cancer Research, London (ICR), and the Royal Marsden NHS Foundation Trust were able to use AI to discover that combining the drug everolimus with another called vandetanib could enhance vandetanib’s capacity to pass through the blood-brain barrier in order to treat the cancer. Why this is important: Initial tests on mice have shown positive results and experts now hope to test the drug combination on a wider group of children in clinical trials. The study showed that combining the two drugs increased the amount of vandetanib in the brains of mice with DIPG by 56%. The team behind the research said the study shows how AI could open up new avenues for cancer treatment by spotting new ways of combining existing medicines. [Click here to find out!]( [Greece Used ML Algorithm for Covid Testing of Travellers]( brief: A prescriptive computer program used by Greece to identify asymptomatic Covid-19 infections in travelers may have slowed the virus’s spread through its borders, a new study indicates. In July 2020, Greece largely reopened to spare its tourism-dependent economy from the devastating impact of long-term shutdowns amid Covid-19. Greece collaborated with USC Marshall and Wharton to create ‘Eva,’ an AI algorithm that uses real-time data to identify high-risk visitors for testing. Evidence shows the algorithm caught nearly twice as many asymptomatic infected travelers as would have been caught if Greece had relied on only travel restrictions and randomised Covid testing. Eva helped authorities sort through massive amounts of data provided by tourists, such as where they planned to stay and visit, as well as the demographics of each traveler. Researchers then programmed Eva to sift through the information and develop profiles of the travelers who were likely infected but asymptomatic. Why this is important: With Eva, Greece tested about 17% of the estimated 41,830 households arriving in or passing through the country every day and nearly doubled the number of infections that a typical randomised testing approach would have captured. “Given that randomized testing requires a large testing supply, Eva offers an impressive alternative,” Kimon Drakopoulos, a USC Marshall assistant professor of data sciences and operations and one of the study’s authors said. [Click here to read on!]( [The Biggest AI Trends for 2022]( In brief: Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. In this article for Forbes, he uses his expertise to look ahead to the coming year and predict the seven trends that are likely to be the biggest in the field of AI for 2022. Marr builds on Google CEO Sundar Pichai’s claim, from earlier this year, that AI’s impact will be even greater than that of fire or electricity on our development as a species and speculates that as we move into 2022 more and more decision making will be done by machines, in ways which are inconceivable to us at the moment. He identifies the likely biggest trends as: The augmented workforce, bigger and better language modeling, AI in cybersecurity, AI and the Metaverse, low-code and no-code AI, autonomous vehicles, and creative AI. Why this is important: It may seem early to be looking to 2022 but as autumn begins, now is a good time to look ahead at what is likely to have a major impact next year. By staying ahead of the curb with stories such as these, we can utilise the resources that SuperDataScience has to offer and ensure we’re leading the pack when it comes to data science and AI. [Click here to discover more!]( [UK Publishes 10-year Plan to Become ‘AI Superpower’]( In brief: The UK government has released its 10-year plan to make the country a global “artificial intelligence superpower,” seeking to rival the likes of the US and China. The ‘National Artificial Intelligence Strategy’ is designed to boost the use of AI among the nation’s businesses, attract international investment into British AI companies and develop the next generation of homegrown tech talent. The National AI Strategy includes a number of programs, reports, and initiatives. Among them, a new National AI Research and Innovation program will be launched as part of an effort to improve coordination and collaboration between the country’s researchers. Elsewhere, another program will specifically aim to support AI development outside London and Southeast England, where much of the nation’s AI efforts are currently concentrated. The government said it may allocate more investment and resources to industries that aren’t yet taking full advantage of AI, such as energy and farming. Why this is important: In last week’s newsletter we explored the news that General Sir Patrick Sanders had said that computer and data scientists were to be prioritised by UK Defense but the announcement of the National Artificial Intelligence Strategy goes a step further towards highlighting Britain’s aims to rival the US and China. [Click here to see the full picture!]( [UK Court of Appeal Rejects AI Inventor Claims]( In brief: The Court of Appeal in London has ruled against the physicist Stephen Thaler’s latest bid to list his AI machine Dabus as an inventor on a patent. In what has become a test case for patent law, Thaler has applied for patents listing Dabus as the inventor in a number of jurisdictions, including the US, Europe, and China as well as the UK. Dabus is a so-called “creativity engine” that uses artificial neural networks to generate and assess new ideas. The High Court in England and Wales sided with the UK Intellectual Property Office last September in refusing the patent applications, stating that Dabus couldn’t be granted a patent on the grounds that it wasn’t a ‘natural person’. Now, the Court of Appeal has found that only a ‘person’ with legal personality can be an inventor and that as Thaler isn’t entitled to the patent. Why this is important: You may recall that back in July we covered the decision in South Africa, when it became the first country to award a patent naming an AI as its inventor and the AI’s owner as the patent's owner when it accepted Thaler’s application. This ruling by the UK Court of Appeal puts Britain at odds with both South Africa and Australia but aligns them with the US ruling on the same matter, showing that this contentious matter is far from resolved. [Click here to find out more!]( [Super Data Science podcast]( In this week's [Super Data Science Podcast](, Rob Trangucci joins us to go in depth on Bayesian statistics and how it has been applied to the COVID-19 pandemic in his PhD work. --------------------------------------------------------------- What is the Data Science Insider? 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