An Improved Hybrid Hierarchical Model for Breast Cancer Detection - Sharma, Vikrant;Vashist, Sheenum;Singh, Gagandeep
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Breast cancer is believed to be one in all most far reaching causes of death among women and second highest reason for deaths among humans. Today millions of women are suffering from breast cancer. It is difficult to detect breast cancer in the early stages due to its dormant nature and very few signs and symptoms. Therefore the main reason behind the diagnosis of breast cancer is to decrease the death rate by achieving accurate results. Hence there is a need to automate the diagnostic process to improve the sensitivity and accuracy of the tests. An artificial intelligence based hierarchical…mehr

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Produktbeschreibung
Breast cancer is believed to be one in all most far reaching causes of death among women and second highest reason for deaths among humans. Today millions of women are suffering from breast cancer. It is difficult to detect breast cancer in the early stages due to its dormant nature and very few signs and symptoms. Therefore the main reason behind the diagnosis of breast cancer is to decrease the death rate by achieving accurate results. Hence there is a need to automate the diagnostic process to improve the sensitivity and accuracy of the tests. An artificial intelligence based hierarchical fuzzy expert system is developed which consists of risk parameters, subjective parameters, mammograms and cancerous cell images to diagnose breast cancer with precise results.
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Autorenporträt
Dr. Vikrant Sharma earned his Ph. D. in Electronics and Communication on the topic performance optimization of multichannel, multigigabit per second DWDM ring from I.K. Gujral Punjab Technical University, Punjab, India. He is Professor and Associate Dean in School of Engineering and Technology, GNA University, Phagwara.