Development of an AI Platform for Advanced Breast Cancer Management.

This article explores the transition from a traditional histopathological examination system to an innovative platform using artificial intelligence (AI) for breast cancer detection from histopathological images in Burkina Faso. The existing system is analyzed in detail, highlighting the steps of querying, sample preparation, analysis by the pathologist, and validation by the physician. From this analysis, the needs and challenges are identified, emphasizing the opportunities for AI to improve the efficiency and accuracy of the diagnosis.

Comparative Analysis of Artificial Intelligence Algorithms for Breast Cancer Detection from Pathological Image in Burkina Faso.

Artificial Intelligence (AI) has revolutionized many fields, including medical imaging. This revolution has enabled the digitization of medical images, the development of algorithms allowing the use of data captured in natural language, and deep learning, enabling the development of algorithms for automatic processing of medical images from massive medical data. In Burkina Faso, early and accurate detection of breast cancer is a significant challenge due to limited resources and lack of specialized expertise.

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

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.