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title:"Breast"

    A Review - Breast Cancer Detection using Deep Learning Methods

    Nath, Srigitha S / Jayapraba, Anjaline / C T, Kalaivani et al. | IEEE | 2022

    Expectation maximization based logistic regression for breast cancer classification

    Rajaguru, Harikumar / Prabhakar, Sunil Kumar | IEEE | 2017

    A Quantitative Approach for Determining Breast Cancer Using Mammography Images

    Shruthi, G.K. / Sunitha, M.R | IEEE | 2018

    Automated Diagnosis of Breast Cancer Using Wavelet Based Entropy Features

    R, Karthiga / K, Narasimhan | IEEE | 2018

    Automatic classification of breast density

    Oliver, A. / Freixenet, J. / Zwiggelaar, R. | IEEE | 2005

    Diagnosis Using Data Mining Algorithms for Malignant Breast Cancer Cell Detection

    Saranya, S. / Sasikala, S. | IEEE | 2020

    The Machine Learning based Optimized Prediction Method for Breast Cancer Detection

    Kumar, Nirdosh / Sharma, Gaurav / Bhargava, Lava | IEEE | 2020

    Raman spectroscopy and breast cancer: looking beyond mammography for the early detection of breast cancer

    Fitzmaurice, M. / Myles, J.L. / Crowe, J.P. et al. | IEEE | 2004

    Convolutional Neural Network for Classification of Histopathology Images for Breast Cancer Detection

    Narayanan, Barath Narayanan / Krishnaraja, Vignesh / Ali, Redha | IEEE | 2019

    Predicting Invasive Ductal Carcinoma in breast histology images using Convolutional Neural Network

    Alghodhaifi, Hesham / Alghodhaifi, Abdulmajeed / Alghodhaifi, Mohammed | IEEE | 2019

    Investigating the breast cancer tissue utilizing semi-supervised learning and similarity measure

    Thirumalai, Chandrasegar / Manzoor, Rashad | IEEE | 2017

    Terahertz pulsed imaging and spectroscopy of breast tumours

    Wallace, V. P. / Pickwell, E. / Fitzgerald, A. J. et al. | IEEE | 2006

    Cost optimization using normal linear regression method for breast cancer Type I skin

    Thirumalai, Chandrasegar / Manzoor, Rashad | IEEE | 2017

    Terahertz imaging of breast cancer, a feasibility study

    Fitzgerald, A.J. / Wallace, V.P. / Pye, R. et al. | IEEE | 2004

    BreastNet: Design and Evaluation of a Deep Learning model for recognizing Breast Cancer from Images

    Subramanian, R. Raja / Ravikiran, Lagisetty / Vamsi, Kotte Sai et al. | IEEE | 2022

    Functional diffuse optical spectroscopy of human breast tissue

    Tromberg, B.J. / Cerussi, A.E. / Jakubowski, D. et al. | IEEE | 2001

    Time-resolved quantitative spectroscopy of breast using random walk theory

    Chernomordik, V. / Gandjbakhche, A.H. | IEEE | 2004

    A Comprehensive Analysis of Prediction of P-Glycoprotein in Tumour Cells, Breast Cancer and Ovarian Cancer Using Machine Learning

    Ram, Mylavarpu Kalyan / Nayak, Rudra Kalyan | IEEE | 2021

    Elastic-scattering spectroscopy for diagnosis of breast cancec concepts and research plans

    Bigio, I.J. / Mourant, J.R. | IEEE | 1997

    An Adaptive Approach to the Segmentation of DCE-MR Images of the Breast: Comparison with Classical Thresholding Algorithms

    Kaleli, Fatih / Aydin, Nizamettin / Ertas, Gokhan et al. | IEEE | 2007

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