-
-
Notifications
You must be signed in to change notification settings - Fork 2
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
全球十大死亡因素 #113
Comments
Disease prediction has become important in a variety of applications such as health insurance, tailored health communication and public health. Disease prediction is usually performed using publically available datasets such as HCUP, NHANES or MDS that were initially designed for health reporting or health cost evaluation but not for disease prediction. In these datasets, medical diagnoses are traditionally arranged in "diagnose-related groups" (DRGs). In this paper we compare the disease prediction based on crisp DRG features with the results obtained employing a new set of features that consist of the fuzzy membership of patient diagnoses in the DRG groups. The fuzzy membership features were computed using an ICD-9 ontological similarity approach. The prediction results obtained on a subset of 9,000 patients from the 2005 HCUP data representing three diseases (diabetes, atherosclerosis and hypertension) using two classifiers (random forest and SVM trained on 21,000 samples) show significant (about 10%) improvement as measured by the area under the ROC curve (AROC). https://github.com/kkandhas/Survival-Rate-prediction-of-Breast-Cancer-Patients-SAS- https://github.com/MattD18/Healthcare-Information-System https://github.com/easwerc/HealthInsurancePlan |
health care cost prediction Health Insurance Plan
|
Identifying Future High Cost Individuals within an Intermediate Cost Population |
CRisk Adjustment of Insurance Premiums in the United States and Implications for People with Disabilitieshttps://www.ncbi.nlm.nih.gov/books/NBK11417/ |
Child and Adolescent Health From 1990 to 2015Findings From the Global Burden of Diseases, Injuries, and Risk Factors 2015 Study
Global Health Estimates 2015: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2015. Geneva, World Health Organization; 2016.
The text was updated successfully, but these errors were encountered: