Breast_Cancer_Diagnosis_Hybrid_Models

This paper discusses how hybrid soft computing models can be used to improve the accuracy and reliability of breast cancer diagnosis. Breast cancer is one of the most common cancers affecting women worldwide, and early detection is critical for improving survival rates. Traditional diagnostic methods rely heavily on radiologists interpreting medical images such as mammograms, ultrasound scans, and MRI, which can sometimes lead to human errors or missed early-stage tumors. 

To address these limitations, the paper explores the use of machine learning and artificial intelligence techniques that assist doctors in analyzing medical imaging data more effectively.

Title: Hybrid Models for Breast Cancer Diagnosis

Author: Viren Kumar

Institute: Parul Institute of Computer Application, Parul University, Vadodara, India