Medical data mining : improving information accessibility using online patient drug reviews
Name
755631510-MIT.pdf
Description
Full printable version
Size
4.16 MB
Format
Adobe PDF
Checksum (MD5)
8f001bb1aee73b16953e9f9f64950a70
Author(s)
Li, Yueyang Alice
Advisor(s)
Stephanie Seneff.
Alternative Title
Improving information accessibility using online patient drug reviews
Date Issued
2011
Publisher
Massachusetts Institute of Technology
Abstract
We address the problem of information accessibility for patients concerned about, pharmaceutical drug side effects and experiences. We create a new corpus of online patient-provided drug reviews and present our initial experiments on that corpus. We detect biases in term distributions that show a statistically significant association between a class of cholesterol-lowering drugs called statins, and a wide range of alarming disorders, including depression, memory loss, and heart failure. We also develop an initial language model for speech recognition in the medical domain, with transcribed data on sample patient comments collected with Amazon Mechanical Turk. Our findings show that patient-reported drug experiences have great potential to empower consumers to make more informed decisions about medical drugs, and our methods will be used to increase information accessibility for consumers.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 85-92).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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