The introduction of artificial intelligence (AI) in breast cancer diagnosis in Burkina Faso represents a significant advancement in the field of healthcare. Faced with the public health issue posed by breast cancer, this study focuses on the use of AI to improve early and accurate detection of this disease from histopathological images. For the implementation of the system, we utilized a customized architecture tailored to our context where image quality is low, based on the convolutional neural networks algorithm from the Keras library of TensorFlow. Subsequently, we developed a platform to facilitate its use. This article aims to present the methodology that was used and the results obtained.

Download full-text PDF

Source
http://dx.doi.org/10.3233/SHTI240494DOI Listing

Publication Analysis

Top Keywords

breast cancer
12
artificial intelligence
8
burkina faso
8
intelligence system
4
system automated
4
automated breast
4
cancer detection
4
detection pathology
4
pathology burkina
4
faso methodology
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!