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Showing papers by "Alan H. Morris published in 2019"


Journal ArticleDOI
01 Nov 2019-Chest
TL;DR: TIR is independently associated with mortality in critically ill patients, particularly those with good antecedent glucose control, particularly in well-controlled patients.

38 citations


Journal ArticleDOI
TL;DR: Critical Care Medicine www.ccmjournal.org 469 *See also p. 331.
Abstract: Critical Care Medicine www.ccmjournal.org 469 *See also p. 331.

4 citations


Proceedings ArticleDOI
30 Dec 2019
TL;DR: Three different alignment strategies for statistical shape modeling and how each strategy affects the stroke prediction capability are explored, showing that alignment strategies that take into account LAA orientation or the inherent natural clustering of the population under study provide significant improvement over global alignment in both qualitative as well as quantitative measures.
Abstract: Evidence suggests that the shape of left atrium appendages (LAA) is a primary indicator in predicting stroke for patients diagnosed with atrial fibrillation (AF). Statistical shape modeling tools used to represent (i.e., parameterize) the underlying LAA variability are of crucial importance to learn shape-based predictors of stroke. Most shape modeling techniques use some form of alignment either as a data pre-processing step or during the modeling step. However, the LAA is a joint anatomy along with left atrium (LA), and the relative position and alignment plays a crucial part in determining risk of stroke. In this paper, we explore different alignment strategies for statistical shape modeling and how each strategy affects the stroke prediction capability. This allows for identifying a unified approach of alignment while analyzing the LAA anatomy for stroke. Here, we study three different alignment strategies, (i) global alignment, (ii) global translational alignment and (iii) cluster based alignment. Our results show that alignment strategies that take into account LAA orientation, i.e., (ii), or the inherent natural clustering of the population under study, i.e., (iii), provide significant improvement over global alignment in both qualitative as well as quantitative measures.

1 citations