Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study

Recent advances in artificial intelligence (AI) have sparked interest in developing explainable AI (XAI) methods for clinical decision support systems, especially in translational research. Although using XAI methods may enhance trust in black-box models, evaluating their effectiveness has been chal...

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Detalles Bibliográficos
Autores principales: Sun, Jimin, Shi, Wenqi, Giuste, Felipe O., Vaghani, Yog S., Tang, Lingzi, Wang, May D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636093/
https://www.ncbi.nlm.nih.gov/pubmed/37945586
http://dx.doi.org/10.1038/s41598-023-46493-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636093/
https://www.ncbi.nlm.nih.gov/pubmed/37945586
http://dx.doi.org/10.1038/s41598-023-46493-2

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