Search (1 results, page 1 of 1)

  • × author_ss:"Shi, J."
  • × author_ss:"Liu, Y."
  1. Liu, Y.; Shi, J.; Chen, Y.: Patient-centered and experience-aware mining for effective adverse drug reaction discovery in online health forums (2018) 0.00
    0.0015337638 = product of:
      0.012270111 = sum of:
        0.012270111 = product of:
          0.03681033 = sum of:
            0.03681033 = weight(_text_:problem in 4114) [ClassicSimilarity], result of:
              0.03681033 = score(doc=4114,freq=2.0), product of:
                0.13082431 = queryWeight, product of:
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.030822188 = queryNorm
                0.28137225 = fieldWeight in 4114, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4114)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    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.