Liu, Y.; Shi, J.; Chen, Y.: Patient-centered and experience-aware mining for effective adverse drug reaction discovery in online health forums (2018)
0.00
0.002269176 = product of:
0.004538352 = sum of:
0.004538352 = product of:
0.009076704 = sum of:
0.009076704 = weight(_text_:a in 4114) [ClassicSimilarity], result of:
0.009076704 = score(doc=4114,freq=10.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.1709182 = fieldWeight in 4114, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=4114)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Adverse Drug Reactions (ADRs) have become a serious health problem and even a leading cause of death in the United States. Pre-marketing clinical trials and traditional post-marketing surveillance using voluntary and spontaneous report systems are insufficient for ADR detection. On the other hand, online health forums provide valuable evidences in a large scale and in a timely fashion through the active participation of patients, caregivers, and doctors. In this article, we present patient-centered and experience-aware mining framework for effective ADR discovery using online health forum data. Our experimental evaluation with both an official ADR knowledge base and human-annotated ground truth verifies the effectiveness of the proposed method for ADR discovery.
- Type
- a
