A comprehensive explainable AI approach for enhancing transparency and interpretability in stroke prediction
Abstract Stroke is among the leading causes of death, especially among old adults. Thus, the mortality rate and severe cerebral disability can be avoided when stroke is diagnosed at its early stages, followed by subsequent treatment. There is no doubt that healthcare specialists can find the necessa...
Saved in:
| Main Authors: | Marwa El-Geneedy, Hossam El-Din Moustafa, Hatem Khater, Seham Abd-Elsamee, Samah A. Gamel |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11263-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Strategies for applying interpretable and explainable AI in real world IoT applications
by: Anber Abraheem Shlash Mohammad, et al.
Published: (2025-06-01) -
A Data Centric HitL Framework for Conducting aSsystematic Error Analysis of NLP Datasets using Explainable AI
by: Ahmed El-Sayed, et al.
Published: (2025-08-01) -
Developing a Transparent Anaemia Prediction Model Empowered With Explainable Artificial Intelligence
by: Muhammad Sajid Farooq, et al.
Published: (2025-01-01) -
Decoding ’Eligibility Unknown’: transparent classification and feature-based reclassification in CAFV analysis
by: Muhammad Amir Khan, et al.
Published: (2025-09-01) -
Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms
by: Yogita Dubey, et al.
Published: (2024-11-01)