Estimation and Conformity Evaluation of Multi-Class Counterfactual Explanations for Chronic Disease Prevention

Information Science, Artificial Intelligence, Medicine, Respiratory System, Environmental and Public Health, Cardiovascular System,
chronic disease prevention   counterfactual explanations   conformal predictions   explainable AI   cardiovascular risk   feature selection  

1. Academic Background and Research Motivation In recent years, Artificial Intelligence (AI) has made tremendous progress in healthcare. From initial uses in assisted diagnosis and risk prediction to the recommendation of personalized intervention plans, AI has become a critical tool for improving the quality and efficiency of medical services. How...

Gliomas Disease Prediction: An Optimized Ensemble Machine Learning-Based Approach

Information Science, Computer Science, Artificial Intelligence, Medicine, Oncology,
brain tumor   glioma   machine learning   feature selection   prognosis   prediction   ensemble model  

Glioma Disease Prediction Based on Optimized Integrated Machine Learning Background and Research Objectives In medical research, gliomas are the most common type of primary brain tumors, encompassing various cancer types with different clinical behaviors and treatment outcomes. Accurate prognosis prediction for glioma patients is crucial for optimi...

Asthma Prediction via Affinity Graph Enhanced Classifier: A Machine Learning Approach Based on Routine Blood Biomarkers

Information Science, Computer Science, Artificial Intelligence, Medicine, Respiratory System, Medical Laboratory Science,
asthma prediction   asthma   affinity graph   feature selection   machine learning  

Asthma Prediction Enhanced by Affinity Graph-Based Classifier: A Machine Learning Approach Using Routine Blood Biomarkers Background Asthma is a chronic respiratory disease that affects approximately 235 million people worldwide. According to the World Health Organization (WHO), the main characteristic of asthma is airway inflammation, leading to s...