Networking.
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 doc...
| Publicado en: | Economist Vol. 375; no. 8432; p. 80 |
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| Formato: | Artículo |
| Publicado: |
Economist Newspaper Limited
6/25/2005
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=17438186&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 17438186 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00130613 ECO jtl: Economist issn: 00130613 maglogo: N pubinfo: dt: 6/25/2005 vid: 375 iid: 8432 pid: 161 pub: Economist Newspaper Limited artinfo: ui: 17438186 ppf: 80 ppct: 0 formats: tig: atl: Networking. aug: su: Artificial neural networks Decision making in clinical medicine Prognosis Cancer treatment Health outcome assessment sug: subj: Artificial neural networks Decision making in clinical medicine Prognosis Cancer treatment Health outcome assessment ab: 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. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2005 holdings: @attributes: islocal: N |
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