Comput Math Methods Med - Evaluation of the diagnostic power of thermography in breast cancer using Bayesian network classifiers.

Tópicos

{ cancer(2502) breast(956) screen(824) }
{ take(945) account(800) differ(722) }
{ state(1844) use(1261) util(961) }
{ signal(2180) analysi(812) frequenc(800) }
{ method(2212) result(1239) propos(1039) }
{ inform(2794) health(2639) internet(1427) }
{ case(1353) use(1143) diagnosi(1136) }
{ risk(3053) factor(974) diseas(938) }
{ can(774) often(719) complex(702) }
{ drug(1928) target(777) effect(648) }
{ model(3404) distribut(989) bayesian(671) }
{ network(2748) neural(1063) input(814) }
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{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Breast cancer is one of the leading causes of death among women worldwide. There are a number of techniques used for diagnosing this disease: mammography, ultrasound, and biopsy, among others. Each of these has well-known advantages and disadvantages. A relatively new method, based on the temperature a tumor may produce, has recently been explored: thermography. In this paper, we will evaluate the diagnostic power of thermography in breast cancer using Bayesian network classifiers. We will show how the information provided by the thermal image can be used in order to characterize patients suspected of having cancer. Our main contribution is the proposal of a score, based on the aforementioned information, that could help distinguish sick patients from healthy ones. Our main results suggest the potential of this technique in such a goal but also show its main limitations that have to be overcome to consider it as an effective diagnosis complementary tool.

Resumo Limpo

breast cancer one lead caus death among women worldwid number techniqu use diagnos diseas mammographi ultrasound biopsi among other wellknown advantag disadvantag relat new method base temperatur tumor may produc recent explor thermographi paper will evalu diagnost power thermographi breast cancer use bayesian network classifi will show inform provid thermal imag can use order character patient suspect cancer main contribut propos score base aforement inform help distinguish sick patient healthi one main result suggest potenti techniqu goal also show main limit overcom consid effect diagnosi complementari tool

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