Deep Learning for the Early Detection of Invasive Ductal Carcinoma in Histopathological Images: Convolutional Neural Network Approach With Transfer Learning.
Journal:
JMIR formative research
Published Date:
Aug 21, 2025
Abstract
BACKGROUND: Invasive ductal carcinoma (IDC) is considered the most common form of breast cancer, accounting for a significant percentage of mortality worldwide. Therefore, its early detection is vital to further improve patients' outcomes and survival rates. However, conventional diagnostic methods in the form of manual histopathological examinations are time-consuming, subjective, and prone to errors. Therefore, there is an urgent need to develop automated solutions for accurate IDC detection in histopathology images to assist pathologists in clinical decision-making.
