@inproceedings{ mendeley_7181129374,
  isauthor = {1},
  abstract = {According to Khan et al, “a review earns the adjective systematic if it is based on a clearly formulated 
question, identifies relevant studies, appraises their quality and summarizes the evidence by use of 
explicit methodology”. Conducting systematic reviews tend to be resource intensive and may suffer from
problems such as publication bias, time-lag bias, duplicate bias, citation bias, and outcome reporting bias. 
This research aims to develop a system to facilitate the creation of systematic reviews. Starting with a 
clinical question, the proposed system will query ClinicalTrial.gov to search published RCTs. The system 
will exploit advanced data analytics techniques to systematically mine clinical trials obtained from the 
ClinicalTrial.gov. From the theoretical perspective, the system provides context for exploring the 
feasibility and efficacy of using advanced analytics techniques for generating machine readable, real time 
medical evidence. From a practical perspective, the system is expected to produce cost efficient medical 
evidence. },
  added = {1411502753},
  year = {2014},
  keywords = {Evidence Based Medicine, Health Information Technology, Medical 
Informatics, Systematic Review, Text Analytics},
  isstarred = {1},
  id = {7181129374},
  discipline = {Computer and Information Science},
  address = {Savannah, USA},
  title = {Leveraging Advanced Analytics to Generate Dynamic Medical Systematic Reviews},
  deletionpending = {0},
  version = {1411502889},
  type = {Conference Proceedings},
  url_mendeley = {http://www.mendeley.com/c/7181129374/p/3507711/prem-timsina-2014-leveraging-advanced-analytics-to-generate-dynamic-medical-systematic-reviews/},
  isread = {0},
  author = {{Prem Timsina} and {Omar F. El-gayar} and {Nevine Nawar}},
  series = {Twentieth Americas Conference on Information Systems (AMCIS'14)},
  url_0 = {http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1540&context=amcis2014},
  modified = {1411502889},
  subdiscipline = {None},
  booktitle = {Twentieth Americas Conference on Information Systems (AMCIS'14)},
  dateaccessed = {23/09/14}
}

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Conducting systematic reviews tend to be resource intensive and may suffer from\nproblems such as publication bias, time-lag bias, duplicate bias, citation bias, and outcome reporting bias. \nThis research aims to develop a system to facilitate the creation of systematic reviews. Starting with a \nclinical question, the proposed system will query ClinicalTrial.gov to search published RCTs. The system \nwill exploit advanced data analytics techniques to systematically mine clinical trials obtained from the \nClinicalTrial.gov. From the theoretical perspective, the system provides context for exploring the \nfeasibility and efficacy of using advanced analytics techniques for generating machine readable, real time \nmedical evidence. 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El-gayar} and {Nevine Nawar}},\n series = {Twentieth Americas Conference on Information Systems (AMCIS'14)},\n url_0 = {http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1540&context=amcis2014},\n modified = {1411502889},\n subdiscipline = {None},\n booktitle = {Twentieth Americas Conference on Information Systems (AMCIS'14)},\n dateaccessed = {23/09/14}\n}","author_short":["and Omar F. El-gayar<nbsp>and Nevine Nawar, .P.T."],"author":["and Omar F. El-gayar and Nevine Nawar, Prem Timsina"],"address":"Savannah, USA","added":"1411502753","abstract":"According to Khan et al, “a review earns the adjective systematic if it is based on a clearly formulated question, identifies relevant studies, appraises their quality and summarizes the evidence by use of explicit methodology”. Conducting systematic reviews tend to be resource intensive and may suffer from problems such as publication bias, time-lag bias, duplicate bias, citation bias, and outcome reporting bias. 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