Search (1 results, page 1 of 1)

  • × author_ss:"Chen, Y."
  • × author_ss:"Liu, Y."
  • × type_ss:"a"
  1. Liu, Y.; Shi, J.; Chen, Y.: Patient-centered and experience-aware mining for effective adverse drug reaction discovery in online health forums (2018) 0.01
    0.0053345575 = product of:
      0.016003672 = sum of:
        0.016003672 = weight(_text_:on in 4114) [ClassicSimilarity], result of:
          0.016003672 = score(doc=4114,freq=2.0), product of:
            0.109763056 = queryWeight, product of:
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.04990557 = queryNorm
            0.14580199 = fieldWeight in 4114, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.199415 = idf(docFreq=13325, maxDocs=44218)
              0.046875 = fieldNorm(doc=4114)
      0.33333334 = coord(1/3)
    
    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.