Breast cancer and infertility are the universal problem, the recorded data from hospitals can be used to develop a decision tree to analyze the risk of breast cancer. Estrogens, Progesterone, FSH and LH are natural hormones that are important in sexual development and other body functions. Circumstances that raise your lifetime estrogen levels or lengthen the amount of time your body gets exposed to these hormones may increase your breast cancer risk. FSH and LH levels, on the other hand, seem to exert dual actions in premenopausal and postmenopausal breast cancer patients. An electronic sensor can detect low levels of estrogen (E2), the primary estrogen hormones, FSH and LH in liquids (BLOOD). The electronic sensor attached to the device senses the presence of these hormones and further tests these hormone levels in bodily fluids using decision tree concept in machine learning. This system senses the amount of these hormones secreted in the women’s body fluid (BLOOD) using electronic sensor connected to the kit. Using decision tree it tests the range of secretion of hormones based on age. When the level of secretion of these hormones is abnormal (less or higher than normal range) it alerts the individual for early diagnosis by sending SMS to their registered mobile number.

Fuzzy logic, MATLAB, Seriousness, Decision supporting system, Tumor, Node, Metastasis, Estrogen

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