AI-Driven Model for Accurate Cancer Diagnosis

Breast cancer is a fast spreading disease in the world. It arises in the lining cells (epithelium) of the ducts (85%) or lobules (15%) in the glandular tissue of the breast. Initially, the cancerous growth is confined to the duct or lobule (“in situ”) where it generally causes no symptoms and has minimal potential for spread (metastasis). Over time, these in situ (stage 0) cancers may progress and invade the surrounding breast tissue (invasive breast cancer) then spread to the nearby lymph nodes (regional metastasis) or to other organs in the body (distant metastasis). If a woman dies from breast cancer, it is because of widespread metastasis. Breast cancer treatment can be highly effective, especially when the disease is identified early. This research discusses an AI model designed to detect breast cancer. The model achieved an impressive accuracy of 98 percent on the used dataset of patients, which indicates its effectiveness in distinguishing between benign and cancerous tumors. This level of accuracy makes it a promising tool for medical professionals and researchers to aid in the identification and diagnosis of tumor-related conditions. The research work demonstrates an advanced application of machine learning in healthcare, showcasing the potential of Artificial Intelligence in achieving high accuracy rates in tumor detection