SHAMSUL

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Record description

Title: SHAMSUL
DOI: https://doi.org/10.82595/scilifelab.eymes-4cp46
Description: Explores interpretability for chest X-ray pathology predictions using methods—Grad-CAM, LIME, SHAP, and LRP. It provides heatmaps and evaluation metrics for better insights into the medical significance of predictions made by deep learning models.
Subjects and keywords: Mass Chest X-Ray
Decision Support Systems, Clinical
Deep Learning
Data Visualization
LDL-Receptor Related Proteins
URL: https://shamsul.serve.scilifelab.se
Source code: https://github.com/anondo1969/SHAMSUL
Docker image: docker.io/mahbub1969/shamsul:v6
Date submitted: 2025-01-09 13:24
Date updated: 2026-08-23 15:37
Date available: 2026-08-23 15:32
Language: English

Version 2:
https://doi.org/10.82595/scilifelab.eymes-4cp46 current

Version 1:
https://doi.org/10.82595/scilifelab.dbhte-z5437

To cite all versions, use the following DOI:
https://doi.org/10.82595/scilifelab.5p7tx-cv218