AIMC Topic: Insurance, Health
Clear Filters Showing 1 to 10 of 14 articles
Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.
American journal of veterinary research
Feb 7, 2025
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.
A robust and interpretable ensemble machine learning model for predicting healthcare insurance fraud.
Scientific reports
Jan 2, 2025
Healthcare insurance fraud imposes a significant financial burden on healthcare systems worldwide, with annual losses reaching billions of dollars. This study aims to improve fraud detection accuracy using machine learning techniques. Our approach co...
Fraud detection in healthcare claims using machine learning: A systematic review.
Artificial intelligence in medicine
Dec 28, 2024
OBJECTIVE: Identifying fraud in healthcare programs is crucial, as an estimated 3%-10% of the total healthcare expenditures are lost to fraudulent activities. This study presents a systematic literature review of machine learning techniques applied t...
Enhancing pharmacist intervention targeting based on patient clustering with unsupervised machine learning.
Expert review of pharmacoeconomics & outcomes research
Sep 23, 2024
OBJECTIVES: Adherence to the American Diabetes Association (ADA) Standards of Medical Care is low. This study aimed to assist pharmacists in identifying patients for diabetes control interventions using unsupervised machine learning.
Diabetes Mellitus
Age Factors
Cluster Analysis
United States
Hypoglycemic Agents
Self Report
Sex Factors
Diabetes Complications
Unsupervised Machine Learning
Insurance, Health
Aged
Adult
Middle Aged
Surveys and Questionnaires
Male
Pharmaceutical Services
Machine Learning
Female
Pharmacists
Professional Role
Humans
Antidiscrimination Law Meets Artificial Intelligence-New Requirements for Health Care Organizations and Insurers.
JAMA health forum
Aug 2, 2024
Machine learning in health financing: benefits, risks and regulatory needs.
Bulletin of the World Health Organization
Dec 8, 2023
There is increasing use of machine learning for the health financing functions (revenue raising, pooling and purchasing), yet evidence lacks for its effects on the universal health coverage (UHC) objectives. This paper provides a synopsis of the use ...
Machine Learning-Based Regression Framework to Predict Health Insurance Premiums.
International journal of environmental research and public health
Jun 28, 2022
Artificial intelligence (AI) and machine learning (ML) in healthcare are approaches to make people's lives easier by anticipating and diagnosing diseases more swiftly than most medical experts. There is a direct link between the insurer and the polic...
Dementia risk predictions from German claims data using methods of machine learning.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Apr 22, 2022
INTRODUCTION: We examined whether German claims data are suitable for dementia risk prediction, how machine learning (ML) compares to classical regression, and what the important predictors for dementia risk are.
Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.
BMC public health
May 1, 2020
BACKGROUND: Risk adjustment models are employed to prevent adverse selection, anticipate budgetary reserve needs, and offer care management services to high-risk individuals. We aimed to address two unknowns about risk adjustment: whether machine lea...
Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance.
Bulletin of the World Health Organization
Feb 25, 2020
Technological advances in big data (large amounts of highly varied data from many different sources that may be processed rapidly), data sciences and artificial intelligence can improve health-system functions and promote personalized care and public...
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