Bosam Guard: Web-Based Breast Cancer Detection

Bosam Guard: Web-Based Breast Cancer Detection

Prof.Hemalatha, Chennuru Sahithi, SiddhuVinay, Chinthareddy Tharun Reddy, Chincholi Ashritha

Malla Reddy University
Hyderabad, Telangana

Abstract— The "Bosom Guard" project represents a pioneering effort in the field of breast cancer detection by seamlessly integrating cutting-edge machine learning techniques with the versatile Flask framework to develop a sophisticated web-based tool. This innovative application aims to significantly enhance the efficiency of breast cancer detection by leveraging a meticulously trained dataset. The Flask-based web application facilitates a user-friendly experience, empowering individuals to effortlessly upload medical images for analysis by the trained machine learning model. The results are promptly displayed on the web page, indicating potential malignancies. This streamlined process contributes to the early detection of breast cancer, a critical factor in positively influencing patient outcomes.

The project's focus on accessibility is evident in its intuitive interface, fostering not only ease of use but also encouraging meaningful discussions between medical professionals and patients. By bridging the gap between technological advancements and healthcare, "Bosom Guard" emerges as a comprehensive solution, seamlessly integrating machine learning, image processing, and web development to offer an accurate and timely breast cancer detection tool. Given the global prevalence and severity of breast cancer, the project addresses key limitations associated with existing detection methods such as mammography and manual clinical examinations. These limitations include elevated costs, limited accessibility, and the inherent potential for human error. "Bosom Guard" not only overcomes these challenges but sets a new standard for the intersection of technology and healthcare, ultimately contributing to early breast cancer detection advancement.