BREAST CANCER DETECTION USING MACHINE LEARNING AND DEEP LEARNING

BREAST CANCER DETECTION USING MACHINE LEARNING AND DEEP LEARNING

PRATIKSHA NATIKAR1,  SIDDESH KT2,  KOTURSWAMY SM3

Student, Department Of MCA, BIET, Davangere[1]

Assistant Professor, Department Of MCA, BIET, Davangere [2]

Assistant Professor, Department Of MCA, BIET, Davangere[3]

ABSTRACT

Most recent data available, breast carcinoma of worldwide, accounting for around 900,000 deaths annually. Early detection and accurate diagnosis can increase the likelihood of positive outcomes and lower the death rate from the condition. In actuality, an early diagnosis can help stop it from spreading and spare the premature victims from getting it. Early detection and appropriate diagnosis can increase the likelihood of favourable results and lower the death rate. But as all centred around the idea of "binary grouping" (malignant and benign; no-cancer and cancer). In this study, we suggest using a computer-aided diagnostic (CAD) system that manages a database to identify and diagnose patients into three classes: non-cancerous, malignant, and no cancer.