Novel Mathematical Models for Investigating Topics in Obesity

Published on Sep 1, 2014in Advances in Nutrition7.24
· DOI :10.3945/an.114.006569
John A. Dawson12
Estimated H-index: 12
(UAB: University of Alabama at Birmingham),
Kevin D. Hall37
Estimated H-index: 37
(NIH: National Institutes of Health)
+ 3 AuthorsSteven B. Heymsfield101
Estimated H-index: 101
(Pennington Biomedical Research Center)
There is limited insight into the mechanisms, progression, and related comorbidities of obesity through simple modeling tools such as linear regression. Keeping in mind the words of the late George E. P. Box that “all models are wrong, some are useful,” this symposium presented 4 useful mathematical models or methodologic refinements. Presenters placed specific emphasis on how these novel models and methodologies can be applied to further our knowledge of the etiology of obesity.
  • References (6)
  • Citations (4)
#1Britta GöbelH-Index: 2
#2Arjun Sanghvi (NIH: National Institutes of Health)H-Index: 4
Last.Kevin D. Hall (NIH: National Institutes of Health)H-Index: 37
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#1John A. Dawson (UAB: University of Alabama at Birmingham)H-Index: 12
#2Emily J. Dhurandhar (UAB: University of Alabama at Birmingham)H-Index: 14
Last.David B. Allison (UAB: University of Alabama at Birmingham)H-Index: 112
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#1Kevin D. Hall (NIH: National Institutes of Health)H-Index: 37
#2Gary Sacks (Deakin University)H-Index: 30
Last.Boydoyd Swinburn (Deakin University)H-Index: 68
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#1Diana M. Thomas (MSU: Montclair State University)H-Index: 26
#2Dale A. Schoeller (UW: University of Wisconsin-Madison)H-Index: 77
Last.Steven B. Heymsfield (MSD: Merck & Co.)H-Index: 101
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