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


Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
22 Aug 2024
Historique:
medline: 23 8 2024
pubmed: 23 8 2024
entrez: 23 8 2024
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 39176822
pii: SHTI240494
doi: 10.3233/SHTI240494
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

638-642

Auteurs

Thomas Alassane Ouattara (TA)

Nazi Boni University, Bobo-Dioulasso, Burkina Faso.
Center for Training and Research in Medical Technology (CFRTM), Burkina Faso.
RETINES/University Côte d'Azur, France.

Seydou Golo Barro (SG)

Nazi Boni University, Bobo-Dioulasso, Burkina Faso.
Center for Training and Research in Medical Technology (CFRTM), Burkina Faso.
RETINES/University Côte d'Azur, France.

Pascal Staccini (P)

RETINES/University Côte d'Azur, France.

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Classifications MeSH