Trials ( IF 2.5 ) Pub Date : 2021-09-06 , DOI: 10.1186/s13063-021-05571-4 E Hope Weissler 1 , Tristan Naumann 2 , Tomas Andersson 3 , Rajesh Ranganath 4 , Olivier Elemento 5 , Yuan Luo 6 , Daniel F Freitag 7 , James Benoit 8 , Michael C Hughes 9 , Faisal Khan 3 , Paul Slater 10 , Khader Shameer 3 , Matthew Roe 11 , Emmette Hutchison 3 , Scott H Kollins 1 , Uli Broedl 12 , Zhaoling Meng 13 , Jennifer L Wong 14 , Lesley Curtis 1 , Erich Huang 1, 15 , Marzyeh Ghassemi 16, 17, 18, 19
Correction to: Trials 22, 537 (2021)
https://doi.org/10.1186/s13063-021-05489-x
Following the publication of the original article [1], we were notified that current affiliations 17, 18 and 19 were erroneously added to the first author rather than the senior author (Marzyeh Ghassemi).
The original article has now been corrected.
- 1.
Weissler, et al. The role of machine learning in clinical research: transforming the future of evidence generation. Trials. 2021;22:537. https://doi.org/10.1186/s13063-021-05489-x.
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Affiliations
Duke Clinical Research Institute, Duke University School of Medicine, Box 2834, Durham, NC, 27701, USA
E. Hope Weissler, Scott H. Kollins, Lesley Curtis & Erich Huang
Microsoft Research, Cambridge, MA, USA
Tristan Naumann
AstraZeneca, Gothenburg, Sweden
Tomas Andersson, Faisal Khan, Khader Shameer & Emmette Hutchison
Courant Institute of Mathematical Science, New York University, New York, NY, USA
Rajesh Ranganath
Englander Institute for Precision Medicine, Weill Cornell Medical College, New York, NY, USA
Olivier Elemento
Northwestern University Clinical and Translational Sciences Institute, Northwestern University, Chicago, IL, USA
Yuan Luo
Division Pharmaceuticals, Open Innovation and Digital Technologies, Bayer AG, Wuppertal, Germany
Daniel F. Freitag
University of Alberta, Edmonton, Alberta, Canada
James Benoit
Department of Computer Science, Tufts University, Medford, MA, USA
Michael C. Hughes
Billion Minds, Inc., Seattle, WA, USA
Paul Slater
Verana Health, San Francisco, CA, USA
Matthew Roe
Boehringer-Ingelheim, Burlington, Canada
Uli Broedl
Sanofi, Cambridge, MA, USA
Zhaoling Meng
Sanofi, Washington, DC, USA
Jennifer L. Wong
Duke Forge, Durham, NC, USA
Erich Huang
Vector Institute, University of Toronto, Toronto, Ontario, Canada
Marzyeh Ghassemi
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, USA
Marzyeh Ghassemi
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, USA
Marzyeh Ghassemi
CIFAR AI Chair, Vector Institute, Toronto, Ontario, Canada
Marzyeh Ghassemi
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Corresponding author
Correspondence to E. Hope Weissler.
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Weissler, E.H., Naumann, T., Andersson, T. et al. Correction to: The role of machine learning in clinical research: transforming the future of evidence generation. Trials 22, 593 (2021). https://doi.org/10.1186/s13063-021-05571-4
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DOI: https://doi.org/10.1186/s13063-021-05571-4
中文翻译:
更正:机器学习在临床研究中的作用:改变证据生成的未来
更正:Trials 22, 537 (2021)
https://doi.org/10.1186/s13063-021-05489-x
在原始文章 [1] 发表后,我们被告知当前的隶属关系 17、18 和 19 被错误地添加到第一作者而不是资深作者 (Marzyeh Ghassemi)。
原文章现已更正。
- 1.
韦斯勒等人。机器学习在临床研究中的作用:改变证据生成的未来。试炼。2021;22:537。https://doi.org/10.1186/s13063-021-05489-x。
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隶属关系
杜克大学医学院杜克临床研究所,Box 2834, Durham, NC, 27701, USA
E. Hope Weissler, Scott H. Kollins, Lesley Curtis & Erich Huang
微软研究院,美国马萨诸塞州剑桥
特里斯坦·瑙曼
阿斯利康,瑞典哥德堡
托马斯·安德森、费萨尔·汗、卡德尔·沙米尔和埃米特·哈奇森
Courant 数学科学研究所,纽约大学,纽约,纽约,美国
拉杰什·兰加纳斯
美国纽约州纽约威尔康奈尔医学院英格兰精准医学研究所
奥利维尔·元素托
西北大学临床和转化科学研究所,西北大学,芝加哥,伊利诺伊州,美国
罗元
德国伍珀塔尔拜耳股份公司制药、开放式创新和数字技术部门
丹尼尔·F·弗赖塔格
加拿大阿尔伯塔省埃德蒙顿阿尔伯塔大学
詹姆斯·班诺特
美国马萨诸塞州梅德福塔夫茨大学计算机科学系
迈克尔·C·休斯
Billion Minds, Inc.,美国华盛顿州西雅图市
保罗·斯莱特
Verana Health,旧金山,加利福尼亚,美国
马修·罗
勃林格殷格翰,伯灵顿,加拿大
乌利·布罗德尔
美国马萨诸塞州剑桥市赛诺菲
孟兆玲
美国华盛顿特区赛诺菲
珍妮弗·L·黄
Duke Forge,达勒姆,北卡罗来纳州,美国
黄奕
加拿大安大略省多伦多市多伦多大学矢量研究所
玛兹耶·加塞米
麻省理工学院电气工程与计算机科学系,剑桥,马萨诸塞州,02139,美国
玛兹耶·加塞米
麻省理工学院医学工程与科学研究所,马萨诸塞州剑桥市,02139,美国
玛兹耶·加塞米
加拿大安大略省多伦多矢量研究所 CIFAR AI 主席
玛兹耶·加塞米
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Weissler, EH, Naumann, T., Andersson, T.等。更正:机器学习在临床研究中的作用:改变证据生成的未来。试验 22, 593 (2021)。https://doi.org/10.1186/s13063-021-05571-4
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DOI : https://doi.org/10.1186/s13063-021-05571-4