Title
Predicting individual disease risk based on medical history
Abstract
The monumental cost of health care, especially for chronic disease treatment, is quickly becoming unmanageable. This crisis has motivated the drive towards preventative medicine, where the primary concern is recognizing disease risk and taking action at the earliest signs. However, universal testing is neither time nor cost efficient. We propose CARE, a Collaborative Assessment and Recommendation Engine, which relies only on a patient's medical history using ICD-9-CM codes in order to predict future diseases risks. CARE uses collaborative filtering to predict each patient's greatest disease risks based on their own medical history and that of similar patients. We also describe an Iterative version, ICARE, which incorporates ensemble concepts for improved performance. These novel systems require no specialized information and provide predictions for medical conditions of all kinds in a single run. We present experimental results on a Medicare dataset, demonstrating that CARE and ICARE perform well at capturing future disease risks.
Year
DOI
Venue
2008
10.1145/1458082.1458185
CIKM
Keywords
Field
DocType
chronic disease treatment,future diseases risk,monumental cost,individual disease risk,medical condition,medical history,disease risk,future disease risk,similar patient,own medical history,greatest disease risk,health care,preventive medicine,ensemble,collaborative filtering
Health care,Data mining,Disease,Collaborative filtering,Computer science,Medical history,Chronic disease,Preventative Medicine,Cost efficiency
Conference
Citations 
PageRank 
References 
30
1.84
5
Authors
5
Name
Order
Citations
PageRank
Darcy Davis11658.56
Nitesh Chawla27257345.79
Nicholas Blumm31067.04
Nicholas A Christakis450836.92
Albert-lászló Barabási546491107.35