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19篇 您的检索式:作者名="MARLENE K"
    题名 作者 年代 出处 被引量
1Overexpression of repressive cAMP response element modulators in high glucose and fatty acid-treated rat islets: a common mechanism for glucose toxicity and lipotoxicity? 显示文摘ZHOU Y P MARLEN K PALMA J F 2003J Biol Chem2003,278,51:1
2Overexpression of Repressive cAMP Response Element Modulators in High Glucose and Fatty Acid-treated Rat Islets显示文摘Zhou YP Marlen K Pama JF 2003J Bio Chem2003,278,51:1
3Identifying antimicrobial resistance genes with DNA microarrys显示文摘Douglas R C Marlene K B Melissa J K 2003Antimicrob Agents Chemother2003,47,10:1
4Cancer Pain Management and the JCAHO’s Pain Standards显示文摘Marlene Zichi Cohen Mary K Easley Coni Ellis Beverly Hughes Kristin Ownby Beverly Green Rashad Mari Rude Ellen Taft Joycelyn Bailey Westbrooks 2003Journal of Pain and Symptom Management2003,,6:1
5Second line chemotherapy in patients with enteropathy-associated T cell lymphoma: a retrospective single center analysis 显示文摘Markus R Marlene T Barbara K 2012Ann Hematol2012,91,1:1
6Effects of a Persuasive Commu-nication on Beliefs,Attitudes,and Career Choice显示文摘Marlene K Strader Barry M Katz 1989The Journalof Social Psychology1989,130,2:1
7Essential of a magnetic work environment:PART 1显示文摘Marlene K Claudia S 2004Nursing2004,34,6:1
8Essential of a magnetic work environment:PART 2显示文摘Marlene K Claudia S 2004Nursing2004,34,7:1
9Essential of a magnetic work environment:PART 3显示文摘Marlene K Claudia S 2004Nursing2004,34,8:1
10Essential of a magnetic work environment:PA R T 4显示文摘Marlene K Claudia S 2004Nursing2004,34,9:1
11An empirical velocity scale relation for modeling a design of large pelagic trawl 显示文摘Ferro R S T Van Marlen B Hansen K E 1996Fisheries Research1996,28,:1
12leptin and reproduction 显示文摘DARRELL W MARLENE F WADE K M 2002Steroids2002,67,2:1
13Slit-Lamp Needle Revision of Failed Filtering Blebs Using High-Dose Mitomycin C显示文摘Rajesh K Shetty Leah Wartluft Marlene R Moster 2005Journal of Glaucoma2005,,1:1
14Comparison of phenotypic and genotypic techniques for identification of unusual aerobic pathogenic gram-negative bacilli显示文摘 Nicole M Ellis Marlene K Hopkins 1998 1998Journal of Clinical Microbiology1998,,:1
15Use of a novel fiber optical strain sensor for monitoring the vertical deflection of an aircraft Flap显示文摘GAIZKA D MARLENE K MICHAEL L 2009IEEE Sensors Journal2009,9,10:1
16Surface structures of supported tungsten oxide catalysts under dehydrated conditions显示文摘DU S K MARLENE OSTROMECKI WACHS I E 1996J Mol Catal A:Chem1996,106,12:1
17Antimicrobial activity of natural agents coated on starch-based films against Staphylococcus aureus 显示文摘Kuorwel K Kuorwel Marlene J Cran Kees Sonneveld 2011Jour- nal of Food Science2011,76,8:1
18Disruption of PPAR[gamma]/[Beta]-catenin-mediated regulation of apelin impairs BMP-induced mouse and human pulmonary arterial EC survival显示文摘Alastalo Tero-Pekka Li Molong Perez Vinicio de Jesus Pham David Sawada Hirofumi Wang Jordon K Koskenvuo Minna Wang Lingli Freeman Bruce A Chang Howard Y Rabinovitch Marlene 2011Journal of Clinical Investigation2011,,9:1
19Prediction of permanent pacemaker implantation after transcatheter aortic valve replacement:The role of machine learning显示文摘BACKGROUND Atrioventricular block requiring permanent pacemaker(PPM)implantation is an important complication of transcatheter aortic valve replacement(TAVR).Application of machine learning could potentially be used to predict preprocedural risk for PPM.AIM To apply machine learning to be used to predict pre-procedural risk for PPM.METHODS A retrospective study of 1200 patients who underwent TAVR(January 2014-December 2017)was performed.964 patients without prior PPM were included for a 30-d analysis and 657 patients without PPM requirement through 30 d were included for a 1-year analysis.After the exclusion of variables with near-zero variance or≥50%missing data,167 variables were included in the random forest gradient boosting algorithm(GBM)optimized using 5-fold cross-validations repeated 10 times.The receiver operator curve(ROC)for the GBM model and PPM risk score models were calculated to predict the risk of PPM at 30 d and 1 year.RESULTS Of 964 patients included in the 30-d analysis without prior PPM,19.6%required PPM post-TAVR.The mean age of patients was 80.9±8.7 years.42.1%were female.Of 657 patients included in the 1-year analysis,the mean age of the patients was 80.7±8.2.Of those,42.6%of patients were female and 26.7%required PPM at 1-year post-TAVR.The area under ROC to predict 30-d and 1-year risk of PPM for the GBM model(0.66 and 0.72)was superior to that of the PPM risk score(0.55 and 0.54)with a P value<0.001.CONCLUSION The GBM model has good discrimination and calibration in identifying patients at high risk of PPM post-TAVR.Pradyumna Agasthi Hasan Ashraf Sai Harika Pujari Marlene Girardo Andrew Tseng Farouk Mookadam Nithin Venepally Matthew R Buras Bishoy Abraham Banveet K Khetarpal Mohamed Allam Siva K Mulpuru MD Mackram F Eleid Kevin L Greason Nirat Beohar John Sweeney David Fortuin David R Jr Holmes Reza Arsanjani 2023World Journal of Cardiology2023,15,3:0
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