IEEE

Predicting Medical Claim Denial Using Logistic Regression and Decision Tree Algorithm

Abstract: This study utilizes decision tree and logistic regression models to explore the factors contributing to medical claim denials and identify areas for improvement. We adapt undersampling ...
IEEE

Heart Disease Prediction Using Decision Tree Variants: A Comparative Analysis

Abstract: Heart diseases (CVDs) persist a precede cause of fatality rate worldwide, necessitating accurate and explainable prediction model for early diagnosis and intercession. This study inquire the ...
Frontiers

Classification of angioedema types using decision tree modeling

Introduction: All angioedema (AE) presents with transient, localized swelling; however, the underlying causes, prognosis, and treatments vary significantly. Consequently, identifying a specific AE ...
Journal of Medical Internet Research

Perspectives of Health Care Professionals on the Use of AI to Support Clinical Decision-Making in the Management of Multiple Long-Term Conditions: Interview Study

Objective: We aimed to explore the perspectives of primary care HCPs on managing MLTC and their attitudes toward using AI tools to support clinical decision-making in MLTC care. Methods: In total, 20 ...
Frontiers

A clinical prediction model for schizophrenia based on machine learning algorithms

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...
Microsoft

Decision Trees with Short Explainable Rules

There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...