Google and UK NHS team up to use AI to improve cancer treatment
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.
Key takeaways
- 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.
- 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.
- DeepMind will analyze 700 anonymized scans from former patients who suffered from head and neck cancers.
Cite or link to this article
Griffin, M. (2016) 'Google and UK NHS team up to use AI to improve cancer treatment', 311 Institute, 5 October. Available at: https://www.311institute.com/google-and-uk-nhs-team-up-to-use-ai-to-improve-cancer-treatment/ (Accessed: 1 October 2026).
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.
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Why does this matter?
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.
About the author
Matthew Griffin Founder, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
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Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 15-time best selling author of the "Codex of the Future" series, Matthew is the Founder and Futurist in Chief of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity program, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- applying machine learning to personalized cancer treatment mskcc.org
Source: first published by the 311 Institute on 5 October 2016. Cite as: Griffin, M. (2016). Google and UK NHS team up to use AI to improve cancer treatment. 311 Institute. https://www.311institute.com/google-and-uk-nhs-team-up-to-use-ai-to-improve-cancer-treatment/
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