A Matrix Factorization Approach to Health Record Data Mining

Author/​Artist
Luo, Dee [Browse]
Format
Senior thesis
Language
English
Description
62 pages

Details

Advisor(s)
Kpotufe, Samory [Browse]
Department
Princeton University. Department of Operations Research and Financial Engineering [Browse]
Class year
2016
Summary note
The increasing use of standardized electronic patient records in the health- care industry over the past few years has given rise to a new field of big data analysis with goals of identifying disease correlations, subgrouping similar pa- tients, and performing medical outcome prediction. Developments in these ar- eas have huge potential to cut spending ine ciencies and boost clinical decision support. This thesis proposes a non-negative matrix factorization approach to clinical data mining, drawing analogies to studies done in the fields of text min- ing and predictive recommender systems. We review effective modifications to the standard algorithm and run experiments on a set of patient claims data.

Supplementary Information