ABSTRACT
This chapter discusses an artificial intelligence (AI)-based diagnostic system developed to predict BI-RADS scores for detecting breast cancer over mammograms. A growing impact of AI technology is being seen in the field of healthcare. Among these impacts is the area of cancer diagnosis, where medical imaging is essential to improve the accuracy of cancer diagnosis in the early stages of cancer. Breast cancer is becoming more common among women, with an alarming rate of one woman in India receiving a diagnosis every four minutes. Although breast cancer is a treatable condition, a good prognosis depends on early detection. Mammograms were the only test available until recently to detect breast cancer. However, mammography is ineffective at finding breast cancer in women of all ages, which results in a high rate of false positive and false negative cases. This has terrible consequences. This study examines how radiologists can utilize AI to detect malignant cells from mammograms. Deep learning algorithms, part of AI, can be quite helpful in improving the precision of cancer detection in its early stages when medical imaging is essential. This experimental study demonstrates how to get around this restriction by applying a deep learning technique called CNN (convolutional neural network). The AI-based model developed can forecast the Bi-rad score, which enables radiologists to make precise diagnoses. With an overall precision of 90%, this prediction model produces results that radiologists can use to make adequate diagnoses.
