Explainable AI for Symptom-Based Detection of Monkeypox: a machine learning approach
Abstract Background Monkeypox, a viral zoonotic disease, is an emerging global health concern, with rising incidence and outbreaks extending beyond its endemic regions in Central and, West Africa and the world. The disease transmits through contact with infected animals and humans, leading to fever,...
Saved in:
| Main Authors: | Gizachew Mulu Setegn, Belayneh Endalamaw Dejene |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-03-01
|
| Series: | BMC Infectious Diseases |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12879-025-10738-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children
by: Gizachew Mulu Setegn, et al.
Published: (2025-03-01) -
Epidemiological Aspects and Basic Directions of the Protective Medications against Monkeypox Development
by: L. F. Stovba, et al.
Published: (2024-05-01) -
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) -
Exploratory Data Analysis of the Monkeypox Virus Using Machine Learning
by: Kiran Dhanaji Kale, et al.
Published: (2024-05-01)