Towards Human–Machine Collaboration in Creating an Evaluation Corpus for Adverse Drug Events in Discharge Summaries of Electronic Medical Records
Tài liệu tham khảo
Pirmohamed, 2004, Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients, BMJ, Br. Med. J., 329, 15, 10.1136/bmj.329.7456.15
1971
Lim, 2006, Development of medical informatics in Singapore – keeping pace with healthcare challenges
Koh, 2012
Hazell, 2006, Under-reporting of adverse drug reactions: a systematic review, Drug Safety, 29, 385, 10.2165/00002018-200629050-00003
Melton, 2005, Automated detection of adverse events using natural language processing of discharge summaries, J. Am. Med. Inform. Assoc., 12, 448, 10.1197/jamia.M1794
Park, 2011, A novel algorithm for detection of adverse drug reaction signals using a hospital electronic medical record database, Pharmacoepidemiol. Drug Saf., 20, 598, 10.1002/pds.2139
Ramirez, 2010, A pharmacovigilance program from laboratory signals for the detection and reporting of serious adverse drug reactions in hospitalized patients, Clin. Pharmacol. Ther., 87, 74, 10.1038/clpt.2009.185
Wang, 2009, Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study, J. Am. Med. Inform. Assoc., 16, 328, 10.1197/jamia.M3028
Waller, 2003, A model for the future conduct of pharmacovigilance, Pharmacoepidemiol. Drug Saf., 12, 17, 10.1002/pds.773
Murdoch, 2013, The inevitable application of big data to health care, JAMA, 309, 1351, 10.1001/jama.2013.393
Gurulingappa, 2012, Extraction of potential adverse drug events from medical case reports, J. Biomed. Semant., 3, 15, 10.1186/2041-1480-3-15
Celi, 2014, From pharmacovigilance to clinical care optimisation, Big Data, 2, 134, 10.1089/big.2014.0008
Eriksson, 2013, Dictionary construction and identification of possible adverse drug events in Danish clinical narrative text, J. Am. Med. Inform. Assoc., 20, 947, 10.1136/amiajnl-2013-001708
Medical Dictionary for Regulatory Activities (MedDRA) Terminology, International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH).
Reynar, 1998
Choi, 2000, Advances in domain independent linear text segmentation
Chapman, 2001, A simple algorithm for identifying negated findings and diseases in discharge summaries, J. Biomed. Inform., 34, 301, 10.1006/jbin.2001.1029
Navarro, 2001, A guided tour to approximate string matching, ACM Comput. Surv., 33, 31, 10.1145/375360.375365
Wagner, 1974, The string-to-string correction problem, J. ACM, 21, 168, 10.1145/321796.321811
Huang, 2015, Promises and challenges of big data computing in health sciences, Big Data Res., 2, 2, 10.1016/j.bdr.2015.02.002
H. Gurulingappa, J. Fluck, M. Hofmann-Apitius, L. Toldo, Identification of adverse drug event assertive sentences in medical case reports, in: The First International Workshop on Knowledge Discovery in Health Care and Medicine, KDHCM'11, Online Proceedings: Athens, Greece, September 9, 2011.
Visweswaran, 2003, Detecting adverse drug events in discharge summaries using variations on the simple Bayes model