PROGNOSIS OF BREAST CANCER USING MACHINE LEARNING TECHNIQUES AND ANALYZING FOOD HABITS OF PAKISTANI WOMEN

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dc.contributor.authorRABBIA IBRAR
dc.date.accessioned2025-10-02T11:16:01Z
dc.date.available2025-10-02T11:16:01Z
dc.date.issued2022
dc.description.abstractBreast cancer is easily occurred in all women due to poor eating habits. The present study examined food risk factors for breast cancer, their association with quality of life and changes in eating habits. The research included 200 women data with histological confirmed invasive breast cancer. This research data consists of different food types of patients. In this study different Machine learning algorithms are used like LR, SVM, CNN, Perceptron, GB, ADA Boost, DT, RF, Multi-perceptron. Everyone have different accuracy we analyzed AD Boost classifier have highest accuracy which is 87.5% due to low quantity of our data set.
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/7713
dc.language.isoen
dc.publisherUMT, Lahore
dc.titlePROGNOSIS OF BREAST CANCER USING MACHINE LEARNING TECHNIQUES AND ANALYZING FOOD HABITS OF PAKISTANI WOMEN
dc.typeThesis
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