Artificial intelligence auxiliary diagnosis and treatment system for breast cancer in developing countries

In many developing countries, a significant number of breast cancer patients are unable to receive timely treatment due to a large population base, high patient numbers, and limited medical resources. This paper proposes a breast cancer assisted diagnosis system based on electronic medical records....

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Vydáno v:Journal of X-ray science and technology Ročník 32; číslo 2; s. 395
Hlavní autoři: Li, Wenxiu, Gou, Fangfang, Wu, Jia
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 01.01.2024
Témata:
Artificial Intelligence
Biomarkers, Tumor
Breast Neoplasms - diagnostic imaging
Breast Neoplasms - therapy
Developing Countries
Female
Humans
Neural Networks, Computer
Breast cancer
cancer staging
attention mechanism
convolutional neural network
auxiliary diagnosis
ISSN:1095-9114, 1095-9114
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Shrnutí:In many developing countries, a significant number of breast cancer patients are unable to receive timely treatment due to a large population base, high patient numbers, and limited medical resources. This paper proposes a breast cancer assisted diagnosis system based on electronic medical records. The goal of this system is to address the limitations of existing systems, which primarily rely on structured electronic records and may miss crucial information stored in unstructured records. The proposed approach is a breast cancer assisted diagnosis system based on electronic medical records. The system utilizes breast cancer enhanced convolutional neural networks with semantic initialization filters (BC-INIT-CNN). It extracts highly relevant tumor markers from unstructured medical records to aid in breast cancer staging diagnosis and effectively utilizes the important information present in unstructured records. The model's performance is assessed using various evaluation metrics. Such as accuracy, ROC curves, and Precision-Recall curves. Comparative analysis demonstrates that the BC-INIT-CNN model outperforms several existing methods in terms of accuracy and computational efficiency. The proposed breast cancer assisted diagnosis system based on BC-INIT-CNN showcases the potential to address the challenges faced by developing countries in providing timely treatment to breast cancer patients. By leveraging unstructured medical records and extracting relevant tumor markers, the system enables accurate staging diagnosis and enhances the utilization of valuable information.
Bibliografie:ObjectType-Article-1
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ISSN:1095-9114
1095-9114
DOI:10.3233/XST-230194