Matthew Griffin, described as “The Adviser behind the Advisers” and a “Young Kurzweil,” is the founder and CEO of the World Futures Forum and the 311 Institute, a global Futures and Deep Futures consultancy working between the dates of 2020 to 2070, and is an award winning futurist, and author of “Codex of the Future” series. Regularly featured in the global media, including AP, BBC, CNBC, Discovery, RT, and Viacom, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew’s recent work includes mentoring Lunar XPrize teams, re-envisioning global education and training with the G20, and helping the world’s largest organisations envision and ideate the future of their products and services, industries, and countries. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Bain & Co, BCG, Credit Suisse, Dell EMC, Dentons, Deloitte, E&Y, GEMS, Huawei, JPMorgan Chase, KPMG, Lego, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, T-Mobile, and many more.
WHY THIS MATTERS IN BRIEF
Machine learning could cut the time it takes to plan a patient’s radiotherapy treatment by hours.
Working out how to zap a tumour with radiation is a laborious process for physicians and Google’s machine learning division, DeepMind, thinks AI can help ease the burden.
When medics apply radiotherapy to a cancer patient, they have to carefully determine which parts of the body should be exposed to radiation in order to kill the tumor while ensuring that as much healthy surrounding tissue as possible is preserved. The process – known as segmentation, requires the doctor to manually draw areas that can and can’t be treated onto a 3D scan of the patient’s tumor site. The process is particularly complex for head and neck cancers, in which the tumor often sits immediately next to many important anatomical features.
Now, though, DeepMind will work with University College Hospital in London to develop an artificial-intelligence system that can automate the process. DeepMind will analyze 700 anonymized scans from former patients who suffered from head and neck cancers. They hope to create an algorithm that can learn how physicians make decisions about this part of the treatment process, ultimately segmenting the scans automatically.
“Clinicians will remain responsible for deciding radiotherapy treatment plans, but it is hoped that the segmentation process could be reduced from up to four hours to around an hour,” said a DeepMind spokesperson.
In time, the DeepMind team hopes, the same algorithm might find application in treating cancers elsewhere in the body.
IBM’s Watson supercomputer has also been applying machine learning to personalized cancer treatment but its approach is a little more by the book – it’s currently drawing on 600,000 medical evidence reports and 1.5 million patient records and clinical trials to help doctors develop better treatment plans for cancer patients.
This isn’t DeepMind’s first foray into medical research, either. In fact, this is the third project that it’s announced in collaboration with the UK’s National Health Service. After coming under fire earlier in the year when an app project appeared to provide DeepMind with free access to 1.6 million patients’ records, the research outfit recently announced that it was helping to spot the early signs of visual degeneration by sifting through a million eye scans – it seems that Google are working their way down the body.