​The machine data challenge cancer researchers face

Machine learning is infiltrating many industries. Marketers are using complex data algorithms to target customers based on their behaviours, while urban planning firms are creating better transport systems, and health organisations are detecting diseases earlier. Last year, Amazon professor of machine learning at the University of Washington, Carlos Guestrin, said that in the next five years, every successful breakthrough app will use these methods at its core. But in the highly complex field of cancer, it’s a more laborious and challenging task, according to professor Mathukumalli Vidayasagar, a US-based control theorist who has been working with machine learning methods since the 1990s. Vidayasagar is a Fellow of the Royal Society at the University of Texas and keynote speaker at the University of Melbourne’s ‘Thinking Machines in the Physical World’ conference…


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