ACO classification of thermogram symmetry features for breast cancer diagnosis

2014 ◽  
Vol 6 (3) ◽  
pp. 207-212 ◽  
Author(s):  
Gerald Schaefer
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis

scholarly journals International Classification of Functioning, Disability, and Health in women with breast cancer: a proposal for measurement instruments

2013 ◽  
Vol 29 (6) ◽  
pp. 1083-1093 ◽  
Author(s):  
Flávia Nascimento de Carvalho ◽  
Rosalina Jorge Koifman ◽  
Anke Bergmann
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
International Classification ◽  
International Classification Of Functioning ◽  
Measurement Instruments ◽  
Therapeutic Approaches ◽  
Disability And Health ◽  
Core Set

The International Classification of Functioning, Disability, and Health (ICF) aims at standardization, but its applicability requires consistent instruments. In Brazil, invasive therapeutic approaches are frequent, leading to functional alterations. The current study thus aimed to identify and discuss instruments capable of measuring ICF core set codes for breast cancer. The review included ICF studies in women with breast cancer diagnosis and studies with the objective of translating and validating instruments for the Brazilian population, and consistent with the codes. Review studies, systematic or not, were excluded. Eight instruments were selected, and the WHOQOL-Bref was the most comprehensive. The use of various instruments showed 19 coinciding codes, and the instruments as a whole covered 58 of the total of 81 codes. The use of multiple instruments is time-consuming, so new studies are needed to propose parsimonious tools capable of measuring functioning in women treated for breast cancer.

scholarly journals Multivariate classification of urine metabolome profiles for breast cancer diagnosis

2010 ◽  
Vol 11 (S2) ◽  
Author(s):  
Younghoon Kim ◽  
Imhoi Koo ◽  
Byung Hwa Jung ◽  
Bong Chul Chung ◽  
Doheon Lee
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Multivariate Classification ◽  
Urine Metabolome

Segmentation of Medical Image Based on Superpixel Boundary Perceptual Convolutional Network in Cancer Diagnosis and Treatment

2021 ◽  
Vol 11 (1) ◽  
pp. 254-260
Author(s):  
Xiaochun Yi ◽  
Jing Hou
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Tumor ◽  
Large Scale ◽  
Breast Cancer Diagnosis ◽  
Tumor Segmentation ◽  
Convolutional Network ◽  
Breast Segmentation ◽  
Individual Classifier

In order to reduce the computational complexity of breast tumor segmentation algorithms and improve the accuracy of breast segmentation, this paper proposes a breast tumor segmentation method based on super pixel boundary perceptual convolutional network. This method first uses super pixel segmentation convolutional network algorithm to segment breast medical images, and then uses region growth algorithm to achieve breast tumor segmentation at super pixel level. The research results show that in the classification of breast tumors, the fusion efficiency based on the classifier level is better than the fusion based on the feature set; the index R proposed and adopted in this paper can effectively select the appropriate individual classifier and generate a better performing integration 06%. Classifier, the accuracy of this classifier is 88.73%, the sensitivity is 97.06%. The method can be used to assist doctors in breast cancer diagnosis, improve the efficiency and accuracy of doctors' work diagnosis, and has certain significance for clinical research and large-scale screening of breast cancer.

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