Achievability to Extract Specific Date Information for Cancer Research

Accurate identification of temporal information such as date is crucial for advancing cancer research which often requires precise date information associated with related cancer events. However, there is a gap for existing natural language processing (NLP) systems to identify dates for specific cancer research studies. Illustrated with two case studies, we investigated the feasibility, evaluated the performances and discussed the challenges of date information extraction for cancer research.

[1]  G. Gustafson,et al.  Comparison of acute and late toxicities for three modern high-dose radiation treatment techniques for localized prostate cancer. , 2012, International journal of radiation oncology, biology, physics.

[2]  Christopher G Chute,et al.  An Information Extraction Framework for Cohort Identification Using Electronic Health Records , 2013, AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science.

[3]  L. Schwartz,et al.  Prognostic factors for survival in previously treated patients with metastatic renal cell carcinoma. , 2004, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[4]  Cui Tao,et al.  Comprehensive temporal information detection from clinical text: medical events, time, and TLINK identification , 2013, J. Am. Medical Informatics Assoc..

[5]  G. Myrdal,et al.  Outcome after lung cancer surgery. Factors predicting early mortality and major morbidity. , 2001, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.

[6]  P. Raich,et al.  Metrics for evaluating patient navigation during cancer diagnosis and treatment , 2011, Cancer.

[7]  Matthew G. Johnson,et al.  Automated detection of follow-up appointments using text mining of discharge records. , 2010, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[8]  J. Emery,et al.  Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review , 2015, British Journal of Cancer.

[9]  Joel D. Martin,et al.  À la Recherche du Temps Perdu: extracting temporal relations from medical text in the 2012 i2b2 NLP challenge , 2013, J. Am. Medical Informatics Assoc..

[10]  A. Hartz,et al.  A comparison of observational studies and randomized, controlled trials. , 2000, The New England journal of medicine.

[11]  Andrea Bezjak,et al.  Stereotactic body radiation therapy for inoperable early stage lung cancer. , 2010, JAMA.

[12]  Philip E. Bourne,et al.  Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review , 2019, J. Am. Medical Informatics Assoc..

[13]  L. Habel,et al.  Post-diagnosis statin use and breast cancer recurrence in a prospective cohort study of early stage breast cancer survivors , 2008, Breast Cancer Research and Treatment.

[14]  B. Rosner,et al.  Weight, weight gain, and survival after breast cancer diagnosis. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[15]  S. Silverman,et al.  From randomized controlled trials to observational studies. , 2009, The American journal of medicine.

[16]  Jun'ichi Tsujii,et al.  An end-to-end system to identify temporal relation in discharge summaries: 2012 i2b2 challenge , 2013, J. Am. Medical Informatics Assoc..

[17]  Santiago G. Moreno,et al.  BMC Medical Research Methodology , 2009 .

[18]  Anna Rumshisky,et al.  Evaluating temporal relations in clinical text: 2012 i2b2 Challenge , 2013, J. Am. Medical Informatics Assoc..

[19]  Chen Lin,et al.  Multilayered temporal modeling for the clinical domain , 2016, J. Am. Medical Informatics Assoc..

[20]  V. Macdonald.  Chemotherapy: managing side effects and safe handling. , 2009, The Canadian veterinary journal = La revue veterinaire canadienne.

[21]  Hsinchun Chen,et al.  MedTime: A temporal information extraction system for clinical narratives , 2013, J. Biomed. Informatics.