Breast cancer early diagnosis based on hybrid strategy

Bio-Medical Materials and Engineering

Volumn 24, Issue 6, 2014, Pages 3397-3404

  Li, Peng ^a   Bi, Tingting ^a   Huang, Jiuling ^a   Li, Siben ^a  

^a HARBIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Clustering sampling; Computer aided diagnosis; Image data mining; Support vector machine

Indexed keywords

ADAPTIVE BOOSTING; ARTIFICIAL INTELLIGENCE; CLUSTERING ALGORITHMS; DATA MINING; DISEASES; GENETIC ALGORITHMS; ROUGH SET THEORY; SUPPORT VECTOR MACHINES;

ATTRIBUTE REDUCTION ALGORITHM; CONFUSION MATRICES; IMAGE DATA MININGS; MACHINE LEARNING METHODS; PREPROCESSING TECHNIQUES; RECEIVER OPERATING CHARACTERISTIC CURVES; REDUNDANT FEATURES; SVM CLASSIFICATION;

COMPUTER AIDED DIAGNOSIS;

BREAST CANCER; CANCER DIAGNOSIS; CLASSIFICATION ALGORITHM; CONFERENCE PAPER; EARLY DIAGNOSIS; GENETIC ALGORITHM; IMAGE PROCESSING; MAMMOGRAPHY; PHYSICIAN; ROUGH SET; ALGORITHM; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; FEMALE; HUMAN; IMAGE QUALITY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

ALGORITHMS; EARLY DETECTION OF CANCER; FEMALE; HUMANS; MAMMOGRAPHY; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINES;

EID: 84907279853     PISSN: 09592989     EISSN: 18783619     Source Type: Journal    
DOI: 10.3233/BME-141163     Document Type: Conference Paper

References (12)

1. M.L. Irwin, C. Duggan, C.Y. Wang et al., Fasting c-peptide levels and death resulting from all causes and breast cancer: The health, eating, activity, and lifestyle study, Journal of Clinical Oncology 1 (2011), 47-53.
2. C. DeSantis, R. Siegel, P. Bandi et al., Breast cancer statistics, A Cancer Journal for Clinicians 6 (2011), 408-418.
3. A. Jemal, F. Bray, M.M. Center et al., Global cancer statistics, A Cancer Journal for Clinicians 2 (2011), 69-90.
4. R. Wiemker, P. Rogalla, T. Blaffert et al., Aspects of computer-aided detection (CAD) and volumetry of pulmonary nodules using multislice CT, The British Journal of Radiology 1 (2014), 46-56.
5. H.D. Cheng, J. Shan, W. Ju et al., Automated breast cancer detection and classification using ultrasound images: A survey, Pattern Recognition 1 (2010), 299-317.
6. J.J. Fenton, L. Abraham, S.H. Taplin et al., Effectiveness of computer-aided detection in community mammography practice, Journal of the National Cancer Institute 7 (2011), 1152-1161.
7. E. Alberdi, A.A. Povyakalo, L. Strigini et al., Use of computer-aided detection (CAD) tools in screening mammography: a multidisciplinary investigation, The British Journal of Radiology 1 (2014), 31-40.
8. M.M. Eltoukhy, I. Faye and B.B. Samir, Breast cancer diagnosis in digital mammogram using multiscale curvelet transform, Computerized Medical Imaging and Graphics 4 (2010), 269-276.
9. M. Khalilia, S. Chakraborty and M. Popescu, Predicting disease risks from highly imbalanced data using random forest, BMC Medical Informatics and Decision Making 7 (2011), 51-64.
10. Y. Qian, J. Liang, W. Pedrycz et al., Positive approximation: an accelerator for attribute reduction in rough set theory, Artificial Intelligence 9 (2010), 597-618.
11. J.H. Morra, Z. Tu, L.G. Apostolova et al., Comparison of AdaBoost and support vector machines for detecting Alzheimer's disease through automated hippocampal segmentation, IEEE Transactions on Medical Imaging 1 (2010), 30-43.
12. X. Robin, N. Turck, A. Hainard et al., pROC: An open-source package for R and S+ to analyze and compare ROC curves, BMC bioinformatics 3 (2011), 77-85.