-
1
-
-
84968746788
-
American Heart Association Statistics Committee; Stroke Statistics Subcommittee, Heart Disease and Stroke Statistics - 2016 Update: A Report from the American Heart Association
-
Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, Das SR, de Ferranti S, Després JP, Fullerton HJ, Howard VJ, Huffman MD, Isasi CR, Jiménez MC, Judd SE, Kissela BM, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Magid DJ, McGuire DK, Mohler ER 3rd, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Rosamond W, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Woo D, Yeh RW, Turner MB, Writing Group Members American Heart Association Statistics Committee; Stroke Statistics Subcommittee, Heart Disease and Stroke Statistics-2016 Update: A Report From the American Heart Association. Circulation 2015 133 38 360
-
(2015)
Circulation
, vol.133
, pp. 38-360
-
-
Mozaffarian, D.1
Benjamin, E.J.2
Go, A.S.3
Arnett, D.K.4
Blaha, M.J.5
Cushman, M.6
Das, S.R.7
De Ferranti, S.8
Després, J.P.9
Fullerton, H.J.10
Howard, V.J.11
Huffman, M.D.12
Isasi, C.R.13
Jiménez, M.C.14
Judd, S.E.15
Kissela, B.M.16
Lichtman, J.H.17
Lisabeth, L.D.18
Liu, S.19
Mackey, R.H.20
Magid, D.J.21
McGuire, D.K.22
Mohler, E.R.23
Moy, C.S.24
Muntner, P.25
Mussolino, M.E.26
Nasir, K.27
Neumar, R.W.28
Nichol, G.29
Palaniappan, L.30
Pandey, D.K.31
Reeves, M.J.32
Rodriguez, C.J.33
Rosamond, W.34
Sorlie, P.D.35
Stein, J.36
Towfighi, A.37
Turan, T.N.38
Virani, S.S.39
Woo, D.40
Yeh, R.W.41
Turner, M.B.42
more..
-
2
-
-
3142745348
-
Trends in heart failure incidence and survival in a community-based population
-
Roger VL, Weston SA, Redfield MM, Hellermann-Homan JP, Killian J, Yawn BP, Jacobsen SJ, Trends in heart failure incidence and survival in a community-based population. JAMA 2004 292 344 350. doi: 10.1001/jama.292.3.344
-
(2004)
JAMA
, vol.292
, pp. 344-350
-
-
Roger, V.L.1
Weston, S.A.2
Redfield, M.M.3
Hellermann-Homan, J.P.4
Killian, J.5
Yawn, B.P.6
Jacobsen, S.J.7
-
4
-
-
84953301379
-
Early detection of heart failure with varying prediction windows by structured and unstructured data in electronic health records
-
Wang Y, Ng K, Byrd RJ, Hu J, Ebadollahi S, Daar Z, deFilippi C, Steinhubl SR, Stewart WF, Early detection of heart failure with varying prediction windows by structured and unstructured data in electronic health records. Conf Proc IEEE Eng Med Biol Soc 2015 2015 2530 2533. doi: 10.1109/EMBC.2015.7318907
-
(2015)
Conf Proc IEEE Eng Med Biol Soc
, vol.2015
, pp. 2530-2533
-
-
Wang, Y.1
Ng, K.2
Byrd, R.J.3
Hu, J.4
Ebadollahi, S.5
Daar, Z.6
DeFilippi, C.7
Steinhubl, S.R.8
Stewart, W.F.9
-
5
-
-
84903893026
-
Prevalence of heart failure signs and symptoms in a large primary care population identified through the use of text and data mining of the electronic health record
-
Vijayakrishnan R, Steinhubl SR, Ng K, Sun J, Byrd RJ, Daar Z, Williams BA, deFilippi C, Ebadollahi S, Stewart WF, Prevalence of heart failure signs and symptoms in a large primary care population identified through the use of text and data mining of the electronic health record. J Card Fail 2014 20 459 464. doi: 10.1016/j.cardfail.2014.03.008
-
(2014)
J Card Fail
, vol.20
, pp. 459-464
-
-
Vijayakrishnan, R.1
Steinhubl, S.R.2
Ng, K.3
Sun, J.4
Byrd, R.J.5
Daar, Z.6
Williams, B.A.7
DeFilippi, C.8
Ebadollahi, S.9
Stewart, W.F.10
-
6
-
-
84919461605
-
Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records
-
Byrd RJ, Steinhubl SR, Sun J, Ebadollahi S, Stewart WF, Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records. Int J Med Inform 2014 83 983 992. doi: 10.1016/j.ijmedinf.2012.12.005
-
(2014)
Int J Med Inform
, vol.83
, pp. 983-992
-
-
Byrd, R.J.1
Steinhubl, S.R.2
Sun, J.3
Ebadollahi, S.4
Stewart, W.F.5
-
7
-
-
84880804037
-
Combining knowledge and data driven insights for identifying risk factors using electronic health records
-
Sun J, Hu J, Luo D, Markatou M, Wang F, Edabollahi S, Steinhubl SE, Daar Z, Stewart WF, Combining knowledge and data driven insights for identifying risk factors using electronic health records. AMIA Annu Symp Proc 2012 2012 901 910
-
(2012)
AMIA Annu Symp Proc
, vol.2012
, pp. 901-910
-
-
Sun, J.1
Hu, J.2
Luo, D.3
Markatou, M.4
Wang, F.5
Edabollahi, S.6
Steinhubl, S.E.7
Daar, Z.8
Stewart, W.F.9
-
8
-
-
84995913617
-
-
February 4,-2016
-
"Epic: Software." [Online]. http://www.epic.com/software-index.php. February 4,-2016
-
-
-
-
9
-
-
84876296249
-
Contemporary prevalence and correlates of incident heart failure with preserved ejection fraction
-
Gurwitz JH, Magid DJ, Smith DH, Goldberg RJ, McManus DD, Allen LA, Saczynski JS, Thorp ML, Hsu G, Sung SH, Go AS, Contemporary prevalence and correlates of incident heart failure with preserved ejection fraction. Am J Med 2013 126 393 400. doi: 10.1016/j.amjmed.2012.10.022
-
(2013)
Am J Med
, vol.126
, pp. 393-400
-
-
Gurwitz, J.H.1
Magid, D.J.2
Smith, D.H.3
Goldberg, R.J.4
McManus, D.D.5
Allen, L.A.6
Saczynski, J.S.7
Thorp, M.L.8
Hsu, G.9
Sung, S.H.10
Go, A.S.11
-
10
-
-
84857857236
-
Impact of noncardiac comorbidities on morbidity and mortality in a predominantly male population with heart failure and preserved versus reduced ejection fraction
-
Ather S, Chan W, Bozkurt B, Aguilar D, Ramasubbu K, Zachariah AA, Wehrens XH, Deswal A, Impact of noncardiac comorbidities on morbidity and mortality in a predominantly male population with heart failure and preserved versus reduced ejection fraction. J Am Coll Cardiol 2012 59 998 1005. doi: 10.1016/j.jacc.2011.11.040
-
(2012)
J Am Coll Cardiol
, vol.59
, pp. 998-1005
-
-
Ather, S.1
Chan, W.2
Bozkurt, B.3
Aguilar, D.4
Ramasubbu, K.5
Zachariah, A.A.6
Wehrens, X.H.7
Deswal, A.8
-
11
-
-
84875243337
-
Using methods from the data-mining and machine-learning literature for disease classification and prediction: A case study examining classification of heart failure subtypes
-
Austin PC, Tu JV, Ho JE, Levy D, Lee DS, Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes. J Clin Epidemiol 2013 66 398 407. doi: 10.1016/j.jclinepi.2012.11.008
-
(2013)
J Clin Epidemiol
, vol.66
, pp. 398-407
-
-
Austin, P.C.1
Tu, J.V.2
Ho, J.E.3
Levy, D.4
Lee, D.S.5
-
12
-
-
84860795133
-
Classification of heart failure in the atherosclerosis risk in communities (ARIC) study: A comparison of diagnostic criteria
-
Rosamond WD, Chang PP, Baggett C, Johnson A, Bertoni AG, Shahar E, Deswal A, Heiss G, Chambless LE, Classification of heart failure in the atherosclerosis risk in communities (ARIC) study: a comparison of diagnostic criteria. Circ Heart Fail 2012 5 152 159. doi: 10.1161/CIRCHEARTFAILURE.111.963199
-
(2012)
Circ Heart Fail
, vol.5
, pp. 152-159
-
-
Rosamond, W.D.1
Chang, P.P.2
Baggett, C.3
Johnson, A.4
Bertoni, A.G.5
Shahar, E.6
Deswal, A.7
Heiss, G.8
Chambless, L.E.9
-
14
-
-
0035478854
-
Random forests
-
Brieman L, Random forests. Mach Learn 2001 45 5 32
-
(2001)
Mach Learn
, vol.45
, pp. 5-32
-
-
Brieman, L.1
-
16
-
-
84995971992
-
-
Accessed February 22, 2016
-
Welcome to Python.org. https://www.python.org/. Accessed February 22, 2016
-
-
-
-
19
-
-
84924295546
-
Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration
-
Singh A, Nadkarni G, Gottesman O, Ellis SB, Bottinger EP, Guttag JV, Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration. J Biomed Inform 2015 53 220 228. doi: 10.1016/j.jbi.2014.11.005
-
(2015)
J Biomed Inform
, vol.53
, pp. 220-228
-
-
Singh, A.1
Nadkarni, G.2
Gottesman, O.3
Ellis, S.B.4
Bottinger, E.P.5
Guttag, J.V.6
-
20
-
-
84924375509
-
Hypoglycemia prediction using machine learning models for patients with type 2 diabetes
-
Sudharsan B, Peeples M, Shomali M, Hypoglycemia prediction using machine learning models for patients with type 2 diabetes. J Diabetes Sci Technol 2015 9 86 90. doi: 10.1177/1932296814554260
-
(2015)
J Diabetes Sci Technol
, vol.9
, pp. 86-90
-
-
Sudharsan, B.1
Peeples, M.2
Shomali, M.3
|