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Items: 1 to 20 of 97


Automated determination of metastases in unstructured radiology reports for eligibility screening in oncology clinical trials.

Petkov VI, Penberthy LT, Dahman BA, Poklepovic A, Gillam CW, McDermott JH.

Exp Biol Med (Maywood). 2013 Dec;238(12):1370-8. doi: 10.1177/1535370213508172. Epub 2013 Oct 9.


Increasing the efficiency of trial-patient matching: automated clinical trial eligibility pre-screening for pediatric oncology patients.

Ni Y, Wright J, Perentesis J, Lingren T, Deleger L, Kaiser M, Kohane I, Solti I.

BMC Med Inform Decis Mak. 2015 Apr 14;15:28. doi: 10.1186/s12911-015-0149-3.


Automated detection of radiology reports that document non-routine communication of critical or significant results.

Lakhani P, Langlotz CP.

J Digit Imaging. 2010 Dec;23(6):647-57. doi: 10.1007/s10278-009-9237-1.


Application of recently developed computer algorithm for automatic classification of unstructured radiology reports: validation study.

Dreyer KJ, Kalra MK, Maher MM, Hurier AM, Asfaw BA, Schultz T, Halpern EF, Thrall JH.

Radiology. 2005 Feb;234(2):323-9. Epub 2004 Dec 10.


Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department.

Ni Y, Kennebeck S, Dexheimer JW, McAneney CM, Tang H, Lingren T, Li Q, Zhai H, Solti I.

J Am Med Inform Assoc. 2015 Jan;22(1):166-78. doi: 10.1136/amiajnl-2014-002887. Epub 2014 Jul 16.


Development of automated detection of radiology reports citing adrenal findings.

Zopf JJ, Langer JM, Boonn WW, Kim W, Zafar HM.

J Digit Imaging. 2012 Feb;25(1):43-9. doi: 10.1007/s10278-011-9425-7.


Automated detection of critical results in radiology reports.

Lakhani P, Kim W, Langlotz CP.

J Digit Imaging. 2012 Feb;25(1):30-6. doi: 10.1007/s10278-011-9426-6.


Clinical utility of serologic testing for celiac disease in ontario: an evidence-based analysis.

Health Quality Ontario.

Ont Health Technol Assess Ser. 2010;10(21):1-111. Epub 2010 Dec 1.


A text processing pipeline to extract recommendations from radiology reports.

Yetisgen-Yildiz M, Gunn ML, Xia F, Payne TH.

J Biomed Inform. 2013 Apr;46(2):354-62. doi: 10.1016/j.jbi.2012.12.005. Epub 2013 Jan 24.


Glaucoma diagnostics.

Geimer SA.

Acta Ophthalmol. 2013 Feb;91 Thesis 1:1-32. doi: 10.1111/aos.12072.


Computer-aided detection; the effect of training databases on detection of subtle breast masses.

Zheng B, Wang X, Lederman D, Tan J, Gur D.

Acad Radiol. 2010 Nov;17(11):1401-8. doi: 10.1016/j.acra.2010.06.009. Epub 2010 Jul 22.


Evaluating predictive modeling algorithms to assess patient eligibility for clinical trials from routine data.

Köpcke F, Lubgan D, Fietkau R, Scholler A, Nau C, Stürzl M, Croner R, Prokosch HU, Toddenroth D.

BMC Med Inform Decis Mak. 2013 Dec 9;13:134. doi: 10.1186/1472-6947-13-134.


Efficacy and cost-effectiveness of an automated screening algorithm in an inpatient clinical trial.

Beauharnais CC, Larkin ME, Zai AH, Boykin EC, Luttrell J, Wexler DJ.

Clin Trials. 2012 Apr;9(2):198-203. doi: 10.1177/1740774511434844. Epub 2012 Feb 3.


Design-phase prediction of potential cancer clinical trial accrual success using a research data mart.

London JW, Balestrucci L, Chatterjee D, Zhan T.

J Am Med Inform Assoc. 2013 Dec;20(e2):e260-6. doi: 10.1136/amiajnl-2013-001846. Epub 2013 Jul 14.


Computational challenges and human factors influencing the design and use of clinical research participant eligibility pre-screening tools.

Pressler TR, Yen PY, Ding J, Liu J, Embi PJ, Payne PR.

BMC Med Inform Decis Mak. 2012 May 30;12:47. doi: 10.1186/1472-6947-12-47.


Development of an automated method for detecting mammographic masses with a partial loss of region.

Hatanaka Y, Hara T, Fujita H, Kasai S, Endo T, Iwase T.

IEEE Trans Med Imaging. 2001 Dec;20(12):1209-14.


Needs assessment for next generation computer-aided mammography reference image databases and evaluation studies.

Horsch A, Hapfelmeier A, Elter M.

Int J Comput Assist Radiol Surg. 2011 Nov;6(6):749-67. doi: 10.1007/s11548-011-0553-9. Epub 2011 Mar 30. Review.


Automated matching software for clinical trials eligibility: measuring efficiency and flexibility.

Penberthy L, Brown R, Puma F, Dahman B.

Contemp Clin Trials. 2010 May;31(3):207-17. doi: 10.1016/j.cct.2010.03.005. Epub 2010 Mar 15.


Sepsis alert and diagnostic system: integrating clinical systems to enhance study coordinator efficiency.

Thompson DS, Oberteuffer R, Dorman T.

Comput Inform Nurs. 2003 Jan-Feb;21(1):22-6; quiz 27-8.

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