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008			190710s2019 ||||| |||| 00| 0 eng d
040			_aDIBRA _bspa _cUVAL _erda
041			_aeng
084			_aM
100	1		_aLondoño Londoño, Diana Lucía. _9227169 _eautora.
245	1	0	_aStatistical discrimination between mammary cancer and mastopathy / _cDiana Lucía Londoño Londoño.
264		1	_aValparaíso : _bUniversidad de Valparaíso, _c2019.
300			_a113 hojas.
502			_6Doctor en Estadística.
520			_aBreast cancer is currently considered a high frequency pathology in the world and one of the causes of higher mortality among women. According to recent statistical data published by the World Health Organisation (WHO), breast cancer accounts for 23% of all cancer related cases and 14% of all cancer related deaths among women worldwide (Zhou et al., 2017). Cancer is a group of diseases that cause cells in the body to change and grow out of control (Albertson and Pinkel, 2003). However, if breast anomalities are detected and diagnosis are made at early stages, studies show that the chances of survival can be greatly improved (Kestener et al., 2001; Martin et al., 1979). Currently the most reliable imaging technique for the detection of such anomalities is Mammography, or X-ray examination, that also plays an important role in control during and after the treatment. The early detection of breast cancer in asymptomatic women using breast screening mammography is currently the most effective imaging technique for the detection of such anomalities to reduce the morbidity and mortality associated with breast cancer (Lauby-Secretan et al., 2015). However, high imprecision and false / rate diagnostics makes problem hard. Mammographies are low dose X-ray projections of the breast, and it is the best method for detecting cancer at the early stage. One of the stages present in the analysis of these mammography views involves the identification and classification of breast lesions, such as breast masses and micro-calcifications. Microcalcification is an effective indicator of early breast cancer (Wang et al., 2016).This identification and classification is usually performed manually by a radiologist, who should give a more accurate diagnosis. Furthermore, efficacy is often highly correlated with radiologist expertise and workload. The interpretation of mammograms is however not an easy task. The mammographic appearance of normal tissue is highly variable and the radiological findings associated with breast cancer can be very complex. On the other hand, it has been estimated that 10−30% of cancers which could have been detected are missed (Martin et al., 1979) and a high percent of the patients that are called back at screening turn out not to have cancer (Kestener et al., 2001)...
650		0	_aMODELOS ESTOCASTICOS _9164962.
650		4	_94766 _aNEOPLASMAS DE LA MAMA.
650		4	_911869 _aINTERPRETACION ESTADISTICA DE DATOS.
650		4	_aVARIABLES ALEATORIAS _916403.
700	1		_aNicolis, Orietta, _eProfesora guía _9203161.
700	1		_aStehlík, Milan, _eProfesor supervisor de tesis _9234070.
710	2		_aUniversidad de Valparaíso (Chile). _bFacultad de Ciencias. _bInstituto de Estadística _9228632.
942			_2ddc _c5
999			_c105476 _d105476