A novel approach for breast cancer detection using optimized ensemble learning framework and XAI

RM Munshi, L Cascone, N Alturki, O Saidani… - Image and Vision …, 2024 - Elsevier
Breast cancer (BC) is a common and highly lethal ailment. It stands as the second leading
contributor to cancer-related deaths in women worldwide. The timely identification of this …

White blood cells classification using multi-fold pre-processing and optimized CNN model

O Saidani, M Umer, N Alturki, A Alshardan, M Kiran… - Scientific Reports, 2024 - nature.com
White blood cells (WBCs) play a vital role in immune responses against infections and
foreign agents. Different WBC types exist, and anomalies within them can indicate diseases …

Improving Healthcare Prediction of Diabetic Patients Using KNN Imputed Features and Tri-Ensemble Model

K Alnowaiser - IEEE Access, 2024 - ieeexplore.ieee.org
Objective: Diabetes ranks as the most prevalent ailment in developing nations. Vital steps to
mitigate the consequences of diabetes include early detection and expert medical …

[HTML][HTML] Clinical applications of artificial intelligence in diabetes management: A bibliometric analysis and comprehensive review

A Daza, AJ Olivos-López, MC Pizarro… - Informatics in Medicine …, 2024 - Elsevier
Background Diabetes is one of the most common pathologies today and has become a
constant problem in public health worldwide. Objective The purpose of this study is to …

Integrated feature selection and ensemble learning for heart disease detection: a 2-tier approach with ALAN and ET-ABDF machine learning model

A Mandula, BS Vijaya Kumar - International Journal of Information …, 2024 - Springer
The findings of this investigation give a novel approach to the forecasting of heart disease.
For the purpose of determining significant features, it is a 2-tier procedure that uses a …

An automated approach to predict diabetic patients using KNN imputation and effective data mining techniques

A Altamimi, AA Alarfaj, M Umer… - BMC Medical Research …, 2024 - Springer
Diabetes is thought to be the most common illness in underdeveloped nations. Early
detection and competent medical care are crucial steps in reducing the effects of diabetes …

A deep neural network prediction method for diabetes based on Kendall's correlation coefficient and attention mechanism

X Qi, Y Lu, Y Shi, H Qi, L Ren - Plos one, 2024 - journals.plos.org
Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels.
It may affect various organs and tissues, and even lead to life-threatening complications …

GKN-Stack: An ensemble deep learning framework for blood glucose forecasting based on medical examination data

L Li, H Zhang, R Song - IEEE Access, 2024 - ieeexplore.ieee.org
Objective: Diabetes patients are closely related to blood glucose levels. Predicting blood
glucose levels through routine blood test data can provide auxiliary diagnosis for diabetes …

Breast cancer detection employing stacked ensemble model with convolutional features

H Karamti, R Alharthi, M Umer, H Shaiba… - Cancer …, 2023 - content.iospress.com
Breast cancer is a major cause of female deaths, especially in underdeveloped countries. It
can be treated if diagnosed early and chances of survival are high if treated appropriately …

Comparison of diabetes pre-risk prediction models

K Han, Q Sun, J He, X Zhang, X Cheng… - … on Future of …, 2024 - spiedigitallibrary.org
In the field of medicine, disease prevention is more important than treatment. Diabetes, as
one of the diseases that are harmful and have a large number of patients, the prediction of …