Breast cancer prediction API helps to predict the possibility for a person to be victim of breast cancer. The API uses randomforest algorithm and have an accuracy of 94 percentage.
Early detection of breast cancer can save a lot of lives especially of mothers; the need for such an intelligent platform for women worldwide to be aware of their breast health is of utmost significance. API provides instructions to self detect symptoms of breast cancer, and from the inferences gathered by the person will be utilised to predict probability of having breast cancer. Pink health of mothers worldwide can keep families together, BREAST CANCER PREDICTION API – envision such an image.
Hospitals and labs can predict probability of patients having breast cancer based on their initial inferences.
Women can avoid costs of unnecessary frequent mammogram tests.
API can be integrated with Hospital Management Software to analyse test results even before a doctor’s inspection.
Symptoms of previous breast cancer patients can be related to women taking tests from the same lab/hospital to compare patterns and predict possibility of breast cancer.
Health apps for phones and health websites can give users higher accuracy predictions of their pink health.
Breast cancer is the most common cancer in women worldwide, despite the high survival rate of early detection of breast cancer one in every 2 women in India diagnosed with later stage breast cancers die from it. It shows light on the importance of predicting breast cancer at a very early stage, women aged between 40 and 70 are most susceptible to breast cancer. Doctors recommend taking periodical mammograms at these ages especially for women of age 45 to 54, every year mammograms should be taken.
Medical tests like mammograms, ultra sound, MRI are costly; their symptom analysis depends on the lumps and colour variations in breast. Not all lumps or colour change necessarily mean that it cancer, a practising physician with experience can only say the difference between them. Artificial Intelligence learns from symptoms which ended up in cancer and those which did not, it can efficiently predict from the symptoms whether the patient might form cancer or not. Primary symptoms of breast cancer often go neglected; a patient could use Breast Cancer Prediction API to know whether there is a need to take medical test depending on the probability predicted by the API.