-
1
-
-
65349143362
-
Prediction of chronic obstructive pulmonary disease (COPD) in asthma patients using electronic medical records
-
(PMC2732240)
-
Himes B.E., Dai Y., Kohane I.S., Weiss S.T., Ramoni M.F. Prediction of chronic obstructive pulmonary disease (COPD) in asthma patients using electronic medical records. J. Am. Med. Inform. Assoc. 2009, 16(3):371-379. (PMC2732240).
-
(2009)
J. Am. Med. Inform. Assoc.
, vol.16
, Issue.3
, pp. 371-379
-
-
Himes, B.E.1
Dai, Y.2
Kohane, I.S.3
Weiss, S.T.4
Ramoni, M.F.5
-
2
-
-
34347326247
-
Network-based analysis of affected biological processes in Type 2 diabetes models
-
Liu M., Liberzon A., Kong S.W., Weil R.L., Park P.J., Kohane I.S., Kasif S. Network-based analysis of affected biological processes in Type 2 diabetes models. PLoS Genet. 2007, 3:1-15. 10.1371/journal.pgen.0030096.
-
(2007)
PLoS Genet.
, vol.3
, pp. 1-15
-
-
Liu, M.1
Liberzon, A.2
Kong, S.W.3
Weil, R.L.4
Park, P.J.5
Kohane, I.S.6
Kasif, S.7
-
3
-
-
79960961204
-
Expression of splicing factor genes is reduced in human obesity: links to altered Lipin 1 splicing and enhanced lipogenesis
-
(PMC3167228)
-
Pihlajamaki J., Itkonen P., Crunkhorn S., Vänttinen M., Dearie F., Boes T., Jimenez-Chillaron J., Lappalainen T., Miettinen P., Park P., Nasser I., Goldfine A.B., Laakso M., Patti M.E. Expression of splicing factor genes is reduced in human obesity: links to altered Lipin 1 splicing and enhanced lipogenesis. Cell Metab. 2011, 14(2):208-218. (PMC3167228).
-
(2011)
Cell Metab.
, vol.14
, Issue.2
, pp. 208-218
-
-
Pihlajamaki, J.1
Itkonen, P.2
Crunkhorn, S.3
Vänttinen, M.4
Dearie, F.5
Boes, T.6
Jimenez-Chillaron, J.7
Lappalainen, T.8
Miettinen, P.9
Park, P.10
Nasser, I.11
Goldfine, A.B.12
Laakso, M.13
Patti, M.E.14
-
4
-
-
34548516061
-
Identifying patient smoking status from medical discharge records
-
Uzuner Ö., Goldstein I., Luo Y., Kohane I. Identifying patient smoking status from medical discharge records. J. Am. Med. Inform. Assoc. 2008, 15(1):14-24.
-
(2008)
J. Am. Med. Inform. Assoc.
, vol.15
, Issue.1
, pp. 14-24
-
-
Uzuner, Ö.1
Goldstein, I.2
Luo, Y.3
Kohane, I.4
-
5
-
-
67649352145
-
Recognizing obesity and co-morbidities in sparse data
-
Uzuner Ö. Recognizing obesity and co-morbidities in sparse data. J. Am. Med. Inform. Assoc. 2009, 16(4):561-570.
-
(2009)
J. Am. Med. Inform. Assoc.
, vol.16
, Issue.4
, pp. 561-570
-
-
Uzuner, Ö.1
-
6
-
-
34548508913
-
Evaluating the state-of-the-art in automatic de-identification
-
Uzuner Ö., Luo Y., Szolovits P. Evaluating the state-of-the-art in automatic de-identification. J. Am. Med. Inform. Assoc. 2007, 14(5):550-563.
-
(2007)
J. Am. Med. Inform. Assoc.
, vol.14
, Issue.5
, pp. 550-563
-
-
Uzuner, Ö.1
Luo, Y.2
Szolovits, P.3
-
8
-
-
80053292637
-
2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text
-
Uzuner Ö., South B.R., Shen S., DuVall S.L. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text. J. Am. Med. Inform. Assoc. 2011, 18:552-556.
-
(2011)
J. Am. Med. Inform. Assoc.
, vol.18
, pp. 552-556
-
-
Uzuner, Ö.1
South, B.R.2
Shen, S.3
DuVall, S.L.4
-
9
-
-
84872234230
-
Evaluating the state of the art in co-reference resolution for electronic medical records
-
Uzuner Ö., Bodnari A., Shen S., Forbush T., Pestian J., South B.R. Evaluating the state of the art in co-reference resolution for electronic medical records. J. Am. Med. Inform. Assoc. 2012, 19(5):786-791.
-
(2012)
J. Am. Med. Inform. Assoc.
, vol.19
, Issue.5
, pp. 786-791
-
-
Uzuner, Ö.1
Bodnari, A.2
Shen, S.3
Forbush, T.4
Pestian, J.5
South, B.R.6
-
10
-
-
84882744737
-
Evaluating temporal relations in clinical text: 2012 i2b2 challenge
-
Sun W., Rumshisky A., Uzuner O. Evaluating temporal relations in clinical text: 2012 i2b2 challenge. J. Am. Med. Inform. Assoc. 2013, 20:806-813.
-
(2013)
J. Am. Med. Inform. Assoc.
, vol.20
, pp. 806-813
-
-
Sun, W.1
Rumshisky, A.2
Uzuner, O.3
-
11
-
-
84951852380
-
Creation of a new longitudinal corpus of clinical narratives
-
Kumar V., Stubbs A., Shaw S., Uzuner Ö. Creation of a new longitudinal corpus of clinical narratives. J. Biomed. Inform. 2015, 58S:S6-S10.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S6-S10
-
-
Kumar, V.1
Stubbs, A.2
Shaw, S.3
Uzuner, Ö.4
-
12
-
-
84951026409
-
Annotating longitudinal clinical narratives for de-identification: the 2014 i2b2/UTHealth Corpus
-
Stubbs A., Uzuner Ö. Annotating longitudinal clinical narratives for de-identification: the 2014 i2b2/UTHealth Corpus. J. Biomed. Inform. 2015, 58S:S20-S29.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S20-S29
-
-
Stubbs, A.1
Uzuner, Ö.2
-
13
-
-
84940054677
-
Automated systems for the de-identification of longitudinal clinical narratives: overview of 2014 i2b2/UTHealth shared task Track 1
-
Stubbs A., Kotfila C., Uzuner Ö. Automated systems for the de-identification of longitudinal clinical narratives: overview of 2014 i2b2/UTHealth shared task Track 1. J. Biomed. Inform. 2015, 58S:S11-S19.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S11-S19
-
-
Stubbs, A.1
Kotfila, C.2
Uzuner, Ö.3
-
14
-
-
84940056554
-
Identifying risk factors for heart disease over time: overview of 2014 i2b2/UTHealth shared task Track 2
-
Stubbs A., Xu H., Kotfila C., Uzuner Ö. Identifying risk factors for heart disease over time: overview of 2014 i2b2/UTHealth shared task Track 2. J. Biomed. Inform. 2015, 58S:S67-S77.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S67-S77
-
-
Stubbs, A.1
Xu, H.2
Kotfila, C.3
Uzuner, Ö.4
-
15
-
-
84940707615
-
Annotating risk factors for heart disease in clinical narratives for diabetic patients
-
Stubbs A., Uzuner Ö. Annotating risk factors for heart disease in clinical narratives for diabetic patients. J. Biomed. Inform. 2015, 58S:S78-S91.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S78-S91
-
-
Stubbs, A.1
Uzuner, Ö.2
-
16
-
-
84938262566
-
Ease of adoption of clinical natural language processing software: an evaluation of five systems
-
Zheng K., Vydiswaran V.G.V., Liu Y., Wang Y., Stubbs A., Uzuner Ö., Gururaj A.E., Bayer S., Aberdeen J., Rumshisky A., Pakhomov S., Liu H., Xu H. Ease of adoption of clinical natural language processing software: an evaluation of five systems. J. Biomed. Inform. 2015, 58S:S189-S196.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S189-S196
-
-
Zheng, K.1
Vydiswaran, V.G.V.2
Liu, Y.3
Wang, Y.4
Stubbs, A.5
Uzuner, Ö.6
Gururaj, A.E.7
Bayer, S.8
Aberdeen, J.9
Rumshisky, A.10
Pakhomov, S.11
Liu, H.12
Xu, H.13
-
17
-
-
84938717641
-
Automatic detection of protected health information from clinic narratives
-
Yang H., Garibaldi J.M. Automatic detection of protected health information from clinic narratives. J. Biomed. Inform. 2015, 58S:S30-S38.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S30-S38
-
-
Yang, H.1
Garibaldi, J.M.2
-
18
-
-
84940726529
-
CRFs based de-identification of medical records
-
He B., Guan Y., Cheng J., Cen K., Hua W. CRFs based de-identification of medical records. J. Biomed. Inform. 2015, 58S:S39-S46.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S39-S46
-
-
He, B.1
Guan, Y.2
Cheng, J.3
Cen, K.4
Hua, W.5
-
19
-
-
84945535937
-
Automatic de-identification of electronic medical records using token-level and character-level conditional random fields
-
Liu Z., Chen Y., Tang B., Wang X., Chen Q., Li H., Wang J., Deng Q., Zhu S. Automatic de-identification of electronic medical records using token-level and character-level conditional random fields. J. Biomed. Inform. 2015, 58S:S47-S52.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S47-S52
-
-
Liu, Z.1
Chen, Y.2
Tang, B.3
Wang, X.4
Chen, Q.5
Li, H.6
Wang, J.7
Deng, Q.8
Zhu, S.9
-
20
-
-
84939864819
-
Combining knowledge- and data-driven methods for de-identification of clinical narratives
-
Dehghan A., Kovacevic A., Karystianis G., Keane J.A., Nenadic G. Combining knowledge- and data-driven methods for de-identification of clinical narratives. J. Biomed. Inform. 2015, 58S:S53-S59.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S53-S59
-
-
Dehghan, A.1
Kovacevic, A.2
Karystianis, G.3
Keane, J.A.4
Nenadic, G.5
-
21
-
-
84957037576
-
Hidden markov model using dirichlet process for de-identification
-
Chen T., Cullen R., Godwin M. Hidden markov model using dirichlet process for de-identification. J. Biomed. Inform. 2015, 58S:S60-S66.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S60-S66
-
-
Chen, T.1
Cullen, R.2
Godwin, M.3
-
22
-
-
84940703244
-
A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases
-
Kotfila C., Uzuner Ö. A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases. J. Biomed. Inform. 2015, 58S:S92-S102.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S92-S102
-
-
Kotfila, C.1
Uzuner, Ö.2
-
23
-
-
84945319813
-
Comparison of UMLS terminologies to identify risk of heart disease using clinical notes
-
Shivade C., Malewadkar P., Fosler-Lussier E., Lai A.M. Comparison of UMLS terminologies to identify risk of heart disease using clinical notes. J. Biomed. Inform. 2015, 58S:S103-S110.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S103-S110
-
-
Shivade, C.1
Malewadkar, P.2
Fosler-Lussier, E.3
Lai, A.M.4
-
24
-
-
84936803802
-
The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs
-
Roberts K., Shooshan S.E., Rodriguez L., Abhyankar S., Kilicoglu H., Demner-Fushman D. The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs. J. Biomed. Inform. 2015, 58S:S111-S119.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S111-S119
-
-
Roberts, K.1
Shooshan, S.E.2
Rodriguez, L.3
Abhyankar, S.4
Kilicoglu, H.5
Demner-Fushman, D.6
-
25
-
-
84937854995
-
Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge
-
Cormack J., Nath C., Milward D., Raja K., Jonnalagadda S.R. Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge. J. Biomed. Inform. 2015, 58S:S120-S127.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S120-S127
-
-
Cormack, J.1
Nath, C.2
Milward, D.3
Raja, K.4
Jonnalagadda, S.R.5
-
26
-
-
84940755209
-
Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes
-
Khalifa A., Meystre S. Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes. J. Biomed. Inform. 2015, 58S:S128-S132.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S128-S132
-
-
Khalifa, A.1
Meystre, S.2
-
27
-
-
84936816696
-
Combining glass box and black box evaluations in the identification of heart disease risk factors and their temporal relations from clinical records
-
Grouin C., Moriceau V., Zweigenbaum P. Combining glass box and black box evaluations in the identification of heart disease risk factors and their temporal relations from clinical records. J. Biomed. Inform. 2015, 58S:S133-S142.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S133-S142
-
-
Grouin, C.1
Moriceau, V.2
Zweigenbaum, P.3
-
28
-
-
84941585295
-
Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models
-
Urbain J. Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models. J. Biomed. Inform. 2015, 58S:S143-S149.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S143-S149
-
-
Urbain, J.1
-
29
-
-
84951776890
-
A Context-aware approach for progression tracking of medical concepts in electronic medical records
-
Chang N.-W., Dai H.-J., Jonnagaddala J., Chen C.-W., Tsai R.T.-H., Hsu W.-L. A Context-aware approach for progression tracking of medical concepts in electronic medical records. J. Biomed. Inform. 2015, 58S:S150-S157.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S150-S157
-
-
Chang, N.-W.1
Dai, H.-J.2
Jonnagaddala, J.3
Chen, C.-W.4
Tsai, R.T.-H.5
Hsu, W.-L.6
-
30
-
-
84941670321
-
An automatic system to identify heart disease risk factors in clinical texts over time
-
Chen Q., Li H., Tang B., Wang X., Liu X., Liu Z., Liu S., Wang W., Deng W., Zhu S., Chen Y., Wang J. An automatic system to identify heart disease risk factors in clinical texts over time. J. Biomed. Inform. 2015, 58S:S158-S163.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S158-S163
-
-
Chen, Q.1
Li, H.2
Tang, B.3
Wang, X.4
Liu, X.5
Liu, Z.6
Liu, S.7
Wang, W.8
Deng, W.9
Zhu, S.10
Chen, Y.11
Wang, J.12
-
31
-
-
84940099418
-
Risk factor detection for heart disease by applying text analytics in electronic medical records
-
Torii M., Fan J.-W., Yang W.-L., Lee T., Wiley M.T., Zisook D.S., Huang Y. Risk factor detection for heart disease by applying text analytics in electronic medical records. J. Biomed. Inform. 2015, 58S:S164-S170.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S164-S170
-
-
Torii, M.1
Fan, J.-W.2
Yang, W.-L.3
Lee, T.4
Wiley, M.T.5
Zisook, D.S.6
Huang, Y.7
-
32
-
-
84945353785
-
A hybrid model for automatic identification of risk factors for heart disease
-
Yang H., Garibaldi J.M. A hybrid model for automatic identification of risk factors for heart disease. J. Biomed. Inform. 2015, 58S:S171-S182.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S171-S182
-
-
Yang, H.1
Garibaldi, J.M.2
-
33
-
-
84939817187
-
Using local lexicalized rules to identify heart disease risk factors in clinical notes
-
Karystianis G., Dehghan A., Kovacevic A., Keane J.A., Nenadic G. Using local lexicalized rules to identify heart disease risk factors in clinical notes. J. Biomed. Inform. 2015, 58S:S183-S188.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S183-S188
-
-
Karystianis, G.1
Dehghan, A.2
Kovacevic, A.3
Keane, J.A.4
Nenadic, G.5
-
34
-
-
84865329277
-
Towards automatic diabetes case detection and ABCS protocol compliance assessment
-
[Epub 2012 May 25]
-
Mishra N.K., Son R.Y., Arnzen J.J. Towards automatic diabetes case detection and ABCS protocol compliance assessment. Clin. Med. Res. 2012, 10(3):106-121. [Epub 2012 May 25]. 10.3121/cmr.2012.1047.
-
(2012)
Clin. Med. Res.
, vol.10
, Issue.3
, pp. 106-121
-
-
Mishra, N.K.1
Son, R.Y.2
Arnzen, J.J.3
-
35
-
-
84886258393
-
Syntactic parsing of clinical text: guideline and corpus development with handling ill-formed sentences
-
[Epub 2013 August 1]
-
Fan J.W., Yang E.W., Jiang M., Prasad R., Loomis R.M., Zisook D.S., Denny J.C., Xu H., Huang Y. Syntactic parsing of clinical text: guideline and corpus development with handling ill-formed sentences. J. Am. Med. Inform. Assoc. 2013, 20(6):1168-1177. [Epub 2013 August 1]. 10.1136/amiajnl-2013-001810.
-
(2013)
J. Am. Med. Inform. Assoc.
, vol.20
, Issue.6
, pp. 1168-1177
-
-
Fan, J.W.1
Yang, E.W.2
Jiang, M.3
Prasad, R.4
Loomis, R.M.5
Zisook, D.S.6
Denny, J.C.7
Xu, H.8
Huang, Y.9
-
36
-
-
84873102400
-
Assertion modeling and its role in clinical phenotype identification
-
[Epub 2012 September 21]
-
Bejan C.A., Vanderwende L., Xia F., Yetisgen-Yildiz M. Assertion modeling and its role in clinical phenotype identification. J. Biomed. Inform. 2013, 46(1):68-74. [Epub 2012 September 21]. 10.1016/j.jbi.2012.09.001.
-
(2013)
J. Biomed. Inform.
, vol.46
, Issue.1
, pp. 68-74
-
-
Bejan, C.A.1
Vanderwende, L.2
Xia, F.3
Yetisgen-Yildiz, M.4
-
37
-
-
84857748686
-
A corpus of clinical narratives annotated with temporal information
-
L. Galescu, N. Blaylock, A corpus of clinical narratives annotated with temporal information, in: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, ACM New York, NY, USA, 2012, pp. 715-720 (ISBN: 978-1-4503-0781-9).
-
(2012)
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, ACM New York, NY, USA
, pp. 715-720
-
-
Galescu, L.1
Blaylock, N.2
-
38
-
-
84977597290
-
Augmenting a deep natural language processing system with UMLS
-
October 25-26, European Bioinformatics Institute, Hinxton, Cambridgeshire, UK
-
M. Swift, N. Blaylock, J. Allen, W. de Beaumont, L. Galescu, H. Jung, Augmenting a deep natural language processing system with UMLS, in: Proceedings of the Fourth International Symposium on Semantic Mining in Biomedicine (SMBM), Poster Session, October 25-26, European Bioinformatics Institute, Hinxton, Cambridgeshire, UK.
-
Proceedings of the Fourth International Symposium on Semantic Mining in Biomedicine (SMBM), Poster Session
-
-
Swift, M.1
Blaylock, N.2
Allen, J.3
de Beaumont, W.4
Galescu, L.5
Jung, H.6
-
39
-
-
84939533532
-
Predicting changes in systolic blood pressure using longitudinal patient records
-
Solomon J.W., Nielsen R.D. Predicting changes in systolic blood pressure using longitudinal patient records. J. Biomed. Inform. 2015, 58S:S197-S202.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S197-S202
-
-
Solomon, J.W.1
Nielsen, R.D.2
-
40
-
-
84940972699
-
Coronary artery disease risk assessment from unstructured electronic health records using text mining
-
Jonnagaddala J., Liaw S.-T., Ray P., Kumar M., Chang N.-W., Dai H.-J. Coronary artery disease risk assessment from unstructured electronic health records using text mining. J. Biomed. Inform. 2015, 58S:S203-S210.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S203-S210
-
-
Jonnagaddala, J.1
Liaw, S.-T.2
Ray, P.3
Kumar, M.4
Chang, N.-W.5
Dai, H.-J.6
-
41
-
-
84946238936
-
Textual inference for eligibility criteria resolution in clinical trials
-
Shivade C., Hebert C., Lopetegui M., de Marneffe M.-C., Fosler-Lussier E., Lai A.M. Textual inference for eligibility criteria resolution in clinical trials. J. Biomed. Inform. 2015, 58S:S211-S218.
-
(2015)
J. Biomed. Inform.
, vol.58S
, pp. S211-S218
-
-
Shivade, C.1
Hebert, C.2
Lopetegui, M.3
de Marneffe, M.-C.4
Fosler-Lussier, E.5
Lai, A.M.6
-
42
-
-
84977567997
-
Data exploration and visualization of risk factors for heart disease from medical documents using non-negative matrix factorization (NMF)
-
Y. Ling, J. Xingpeng, Y. An, X. Hu, Data exploration and visualization of risk factors for heart disease from medical documents using non-negative matrix factorization (NMF), in: Seventh i2b2 Shared Task and Workshop, Washington, DC, November 14, 2014.
-
(2014)
Seventh i2b2 Shared Task and Workshop, Washington, DC, November 14
-
-
Ling, Y.1
Xingpeng, J.2
An, Y.3
Hu, X.4
-
43
-
-
84977535450
-
-
Seventh i2b2 Shared Task and Workshop, Washington, DC, November 14
-
C. Grouin, Identification of medication side effects in clinical records: an experiment based on the 2014 i2b2/UTHealth corpus, in: Seventh i2b2 Shared Task and Workshop, Washington, DC, November 14, 2014.
-
(2014)
Identification of medication side effects in clinical records: an experiment based on the 2014 i2b2/UTHealth corpus
-
-
Grouin, C.1
|