[HTML][HTML] Fully interpretable deep learning model using IR thermal images for possible breast cancer cases
Breast cancer remains a global health problem requiring effective diagnostic methods for
early detection, in order to achieve the World Health Organization's ultimate goal of breast …
early detection, in order to achieve the World Health Organization's ultimate goal of breast …
Review of AI & XAI-based breast cancer diagnosis methods using various imaging modalities
R Karthiga, K Narasimhan, R Amirtharajan - Multimedia Tools and …, 2024 - Springer
Breast cancer is a significant health concern; early detection and treatment are critical to
improving patient outcomes. Artificial Intelligence has the potential to assist healthcare …
improving patient outcomes. Artificial Intelligence has the potential to assist healthcare …
GRAPHITE: Graph-Based Interpretable Tissue Examination for Enhanced Explainability in Breast Cancer Histopathology
RK Mondol, EKA Millar, PH Graham, L Browne… - arXiv preprint arXiv …, 2025 - arxiv.org
Explainable AI (XAI) in medical histopathology is essential for enhancing the interpretability
and clinical trustworthiness of deep learning models in cancer diagnosis. However, the …
and clinical trustworthiness of deep learning models in cancer diagnosis. However, the …
[PDF][PDF] Further Development and Validation of an Interpretable Deep Learning Model for IR Image Based Breast Cancer Diagnosis
Breast cancer remains a global health problem requiring effective diagnostic methods for
early detection in order to achieve WHO's ultimate goal of breast self-examination (BSE). A …
early detection in order to achieve WHO's ultimate goal of breast self-examination (BSE). A …