Breast Cancer is the second leading cause of cancer death among women.¹
The chance that a woman will die from breast cancer is about 1 in 39.¹
Because breast cancer may not always show clear signs/symptoms in its early stages, malignant tumors can go undiscovered for a long period of time.
One of the biggest challenges faced in the fight against breast cancer is late-stage diagnosis.
Unquestionably, the most important prognostic element for breast cancer is an early diagnosis.²
Fortunately, thanks to advances in Healthcare Technology and AI physicians are now able to detect cancerous tumors earlier than ever before.
In this article we’ll explore how Machine Learning can be used to detect cancerous tumors.
Classification is a task that requires the use of machine learning algorithms that learn how to assign a class label to examples from the problem domain. An easy to understand example is classifying emails as “spam” or “not spam.”³
Similarly, we’ll use ML classification to flag tumors as malignant or benign (cancerous or non-cancerous).
Machine Learning has the potential to be a disruptor in the Medical Field. Early diagnosis of cancerous tumors can save countless lives and, as technology advances, physicians have more tools available to effectively treat cancerous tumors earlier than ever before.