In this paper, we use feed forward neural networks with the back-propagation algorithm to build decision models for five insurances including life, annuity, health, accident, and investment-oriented insurances. Six features were selected for the inputs of the neural networks including age, sex, annual income, educational level, occupation, and risk preference. Three hundred insurants from an in...

Purpose: The purpose of the project was to develop a new format that accelerates the process of solving structural, regional health care problems and the translation of innovative medical processes into broad clinical practice. Content: The format ‘Regional Product Factory’ (RPF) realizes this objective by uniting the different stake holders of health care transactions, e.g. clinicians, statuto...

In this paper, we use decision trees to establish the decision models for insurance purchases. Five major types of insurances are involved in this study including life, annuity, health, accident, and investment-oriented insurances. Four decision tree methods were used to build the decision models including Chi-square Automatic Interaction Detector (CHAID), Exhaustive Chi-square Automatic Intera...

BACKGROUND We aimed to investigate the management of hypertension in Shanghai, China and to examine whether there was any difference of hypertension management among people enrolled in different health insurances. METHODS In this cross-sectional study, a total of 31,531 residents were selected in Shanghai, using a randomized, stratified, multi-stage sampling method, and were asked to provide ...

abstract: background: today one of the main problems low or middle income families face is financing healthcare costs. this article studies the methods of of financing health care costs among hospitalized diabetic patients in different types of insurances. materials & methods: this is a causal-comparative study. the variables consist of comparative (health care costs) and categorical(different ...

In this paper, we use feed forward neural networks with the back-propagation algorithm to build decision models for five insurances including life, annuity, health, accident, and investment-oriented insurances. Six features (variables) were selected for the inputs of the neural networks including age, sex, annual income, educational level, occupation, and risk preference. Three hundred insurant...