IT IS more than a year since Watson, IBM鈥檚 famous supercomputer, opened a new frontier for artificial intelligence by beating human champions of the quiz show Jeopardy!. Now Watson is learning to use its language skills to help doctors diagnose patients.
Progress is most advanced in cancer care, where IBM is working with several US hospitals to build a virtual physicians鈥� assistant. 鈥淚t鈥檚 a machine that can read everything and forget nothing,鈥� says , a doctor at the Memorial Sloan-Kettering Cancer Center in New York, who is collaborating with IBM.
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When playing Jeopardy!, analysed each question in a bid to guess what it was about. Then it looked for possible answers in its database, made up of sources such as encyclopaedias, scoring each according to the evidence associated with it and answering with the highest rated answer. The system takes a similar approach when dealing with medical questions, although in this case it draws on information from medical journals and clinical guidelines.
To test the system, Watson was first tasked with answering questions taken from Doctor鈥檚 Dilemma, a competition for trainee doctors that takes place at the annual meeting of the American College of Physicians. Watson was given 188 questions that it had not seen before and achieved around 50 per cent accuracy 鈥� not bad for an early test, but hardly ideal ().
To improve, Watson is now absorbing records 鈥� tens of thousands at Sloan-Kettering alone 鈥� of treatments and outcomes associated with individual patients. Given data on a new patient, Watson looks for information on those with similar symptoms, as well as the treatments that have been the most successful. The idea is it will give doctors a range of possible diagnoses and treatment options, each with an associated level of confidence. The result will be a system that its creators say can suggest nuanced treatment plans that take into account factors like drug interactions and a patient鈥檚 medical history.
鈥淲atson will give doctors a range of possible diagnoses and treatment options to choose from鈥�
William Audeh, a doctor at Cedars-Sinai Medical Center in Los Angeles, who is working with IBM, says the last few months have involved 鈥渇illing Watson鈥檚 brain鈥� with medical data. Watson is answering basic questions based on the treatment guidelines that are published by medical societies and is showing 鈥渧ery positive鈥� results, he adds.
The technology is particularly useful in oncology because doctors struggle to keep up with the explosion of genomic and molecular data generated about each cancer type. This means it can take years for findings to translate into medical practice. By contrast, Watson can absorb new results and relay them to doctors quickly, together with an estimate of their potential usefulness. 鈥淲atson really has great potential,鈥� says Audeh. 鈥淐ancer needs it most because it鈥檚 becoming so complicated so quickly.鈥�
The IBM system could also approve treatment requests more quickly. At WellPoint, one of the largest insurers in the US, nurses use guidelines and patient history to determine if a request is in line with company policy. Nurses are now training Watson by feeding it test requests and observing the answers. Progress is good and the system could be deployed next year, says WellPoint鈥檚 Cindy Wakefield. 鈥淣ow it can take up to a couple of days,鈥� she says. 鈥淲e hope Watson can return the accurate recommendation in a matter of minutes.鈥�
Preparing for your financial future
Is your pension invested in the best possible way? To answer this question involves weighing up multiple investment options, future income prospects and the experience of others in similar situations. It is the kind of problem that most people struggle with, but which IBM鈥檚 supercomputer Watson may be able to tackle.
IBM announced in May that it has partnered with Citi, a multinational bank, to explore the idea of training Watson as a financial adviser. It is still early days, but IBM thinks that three-way conversations, in which financial advisers put questions to Watson about the options open to a customer, could result in people making better financial decisions.
