Year: 2025
Type: article
Abstract: Developing a breast cancer detection solution using Python, Flask, HTML, CSS, and machine learning. Employing pandas and NumPy for data manipulation, while utilizing matplotlib and seaborn for insightful visualization to enhance model training and diagnostic accuracy. The system offers a user-friendly web interface allowing users to input clinical data for analysis. Through sophisticated data preprocessing and feature extraction methods, combined with powerful machine learning algorithms, including logistic regression and support vector machines, the system provides accurate predictions regarding the presence of breast cancer. The integration of Matplotlib and Seaborn enables the generation of insightful visualizations, enhancing the interpretability of the model predictions. Future iterations may focus on refining the model's performance and incorporating additional features to further enhance its clinical utility.
Authors: Zaara Naikwadi, Anushka More, Mehreen Fatma, Somali Deshpande, Anup Vanage
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410099815