Artificial Intelligence System for Automated Breast Cancer Detection in Pathology in Burkina Faso: Methodology Overview.

Journal: Studies in health technology and informatics
Published Date:

Abstract

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.

Authors

  • Thomas Alassane Ouattara
    Nazi Boni University, Bobo-Dioulasso, Burkina Faso.
  • Seydou Golo Barro
    Nazi Boni University, Bobo-Dioulasso, Burkina Faso.
  • Pascal Staccini
    IRIS Department, URE RETINES, Faculté de Médecine, Université Côte d'Azur, France.