dc.contributor.author | Cabrera, Reuben Joseph | |
dc.date.accessioned | 2019-08-13T17:57:29Z | |
dc.date.available | 2019-08-13T17:57:29Z | |
dc.date.issued | 2018-06 | |
dc.identifier.uri | http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/443 | |
dc.description.abstract | Electronic medical records have made data collection e fficient allowing health professionals and researchers to analyze patient records faster. CHITS, the first EMR in the Philippines has collected millions of data across diff erent areas in Luzon however, CHITS does not contain any data analysis module. This project aims to make use of the large amount of data available in CHITS by developing a diabetes recommender system with big data analytics. The system recommends treatments by finding similar patients by analyzing patient pro files through the use of a similarity metric called Cosine Similarity. | en_US |
dc.language.iso | en | en_US |
dc.subject | Recommender System | en_US |
dc.subject | Big Data Analytics | en_US |
dc.subject | Cosine Similarity | en_US |
dc.title | CHITS Diabetes Data Warehouse with Big Data Analytics | en_US |
dc.type | Thesis | en_US |