@inproceedings{25c89fbb26034b5890aad17c1e4bf88c,
title = "Mining officially unrecognized side effects of drugs by combining web search and machine learning",
abstract = "We consider the problem of finding officially unrecognized side effects of drugs. By submitting queries to the Web involving a given drug name, it is possible to retrieve pages concerning the drug. However, many retrieved pages are irrelevant and some relevant pages are not retrieved. More relevant pages can be obtained by adding the active ingredient of the drug to the query. In order to eliminate irrelevant pages, we propose a machine learning process to filter out the undesirable pages. The process is shown experimentally to be very effective. Since obtaining training data for the machine learning process can be time consuming and expensive, we provide an automatic method to generate the training data. The method is also shown to be very accurate. The side effects of three drugs which are not recognized by FDA are validated by an expert. We believe that the same approach can be applied to many real life problems and will yield high precision. Thus, this could lead a new way to perform retrieval with high accuracy.",
keywords = "Accurate retrieval, Machine learning, Mining side effects of drugs, Precision",
author = "Carlo Carino and Yuanyuan Jia and Bruce Lambert and West, {Patricia M.} and Clement Yu",
year = "2005",
language = "English (US)",
isbn = "1595931406",
series = "International Conference on Information and Knowledge Management, Proceedings",
pages = "365--372",
booktitle = "CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management",
note = "CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management ; Conference date: 31-10-2005 Through 05-11-2005",
}