| Sumario: | The article reports research on cancer prognosis, using a neural computer network. A group of particle physicists led by Robin Marshall of the University of Manchester, in Britain, has applied its knowledge of information technology to show how computer programs known as neural networks can help doctors to choose the best treatments for people with cancer. Unlike a conventional computer, which takes data, processes it using an algorithm and generates a definite answer, a neural network learns to create a range of answers from a range of inputs. Dr Marshall has turned this expertise to the medical field, following a chance meeting with Sir Alfred Cuschieri, an oncologist at Ninewells Hospital in Dundee. Dr Marshall and Sir Alfred, together with some colleagues from Manchester and Dundee universities, selected records that contained enough data to create a detailed profile of a patient at the beginning of his treatment, and to follow his progress over the subsequent five years. The researchers, who will publish their work in a forthcoming issue of Concurrency and Computation: Practice and Experience, then tested the trained network. According to Sir Alfred, this system is ideally suited to predicting the survival chances of individuals. He says that the statistical techniques currently used by doctors to calculate a person's chances of surviving a disease such as cancer are a blunt instrument. By contrast, the neural network created at Manchester enables them to give individual prognoses, so they do not have to rely on crudely defined average chances of survival. The researchers also believe that their system could be applied to the treatment of a variety of other chronic disorders, such as heart disease and diabetes.
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