Developing a Transparent Anaemia Prediction Model Empowered With Explainable Artificial Intelligence
The worldwide health epidemic of anaemia which is a condition with low levels of red blood cells or haemoglobin requires accurate prediction models to act promptly and improve patient outcomes because it is widespread and has different causes. The effective management of anaemia is piled with obstru...
Saved in:
Main Authors: | Muhammad Sajid Farooq, Muhammad Hassan Ghulam Muhammad, Oualid Ali, Zahid Zeeshan, Muhammad Saleem, Munir Ahmad, Sagheer Abbas, Muhammad Adnan Khan, Taher M. Ghazal |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10813340/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Towards Transparent Diabetes Prediction: Combining AutoML and Explainable AI for Improved Clinical Insights
by: Raza Hasan, et al.
Published: (2024-12-01) -
Exploring Early Learning Challenges in Children Utilizing Statistical and Explainable Machine Learning
by: Mithila Akter Mim, et al.
Published: (2025-01-01) -
An explainable Bi-LSTM model for winter wheat yield prediction
by: Abhasha Joshi, et al.
Published: (2025-01-01) -
PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations
by: Fahmida Khanom, et al.
Published: (2025-01-01) -
Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME
by: Md. Manowarul Islam, et al.
Published: (2025-01-01)