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643 results on '"Tannenbaum, Allen"'

13. The glymphatic system: Current understanding and modeling

Author

Bohr, Tomas, Hjorth, Poul G., Holst, Sebastian C., Hrabětová, Sabina, Kiviniemi, Vesa, Lilius, Tuomas, Lundgaard, Iben, Mardal, Kent-Andre, Martens, Erik A., Mori, Yuki, Nägerl, U. Valentin, Nicholson, Charles, Tannenbaum, Allen, Thomas, John H., Tithof, Jeffrey, Benveniste, Helene, Iliff, Jeffrey J., Kelley, Douglas H., and Nedergaard, Maiken

Published
2022
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32. Unbalanced Regularized Optimal Mass Transport with Applications to Fluid Flows in the Brain

Author

Chen, Xinan, Benveniste, Helene, and Tannenbaum, Allen R.

Subjects
FOS: Mathematics, Numerical Analysis (math.NA), Mathematics - Numerical Analysis
Abstract

As a generalization of the optimal mass transport (OMT) approach of Benamou and Brenier's, the regularized optimal mass transport (rOMT) formulates a transport problem from an initial mass configuration to another with the optimality defined by the total kinetic energy, but subject to an advection-diffusion constraint equation. Both rOMT and the Benamou and Brenier's formulation require the total initial and final masses to be equal; mass is preserved during the entire transport process. However, for many applications, e.g., in dynamic image tracking, this constraint is rarely if ever satisfied. Therefore, we propose to employ an unbalanced version of rOMT to remove this constraint together with a detailed numerical solution procedure with applications to analyzing fluid flows in the brain., 19 pages, 5 figures

Published
2023

35. Improved prediction of drug-induced liver injury literature using natural language processing and machine learning methods.

Author

Jung Hun Oh, Tannenbaum, Allen, and Deasy, Joseph O.

Subjects
MACHINE learning, SCIENTIFIC literature, LIVER injuries, PROGRAMMING languages, DRUG side effects, NATURAL language processing
Abstract

Drug-induced liver injury (DILI) is an adverse hepatic drug reaction that can potentially lead to life-threatening liver failure. Previously published work in the scientific literature on DILI has provided valuable insights for the understanding of hepatotoxicity as well as drug development. However, the manual search of scientific literature in PubMed is laborious and time-consuming. Natural language processing (NLP) techniques along with artificial intelligence/machine learning approaches may allow for automatic processing in identifying DILIrelated literature, but useful methods are yet to be demonstrated. To address this issue, we have developed an integrated NLP/machine learning classification model to identify DILI-related literature using only paper titles and abstracts. For prediction modeling, we used 14,203 publications provided by the Critical Assessment of Massive Data Analysis (CAMDA) challenge, employing word vectorization techniques in NLP in conjunction with machine learning methods. Classification modeling was performed using 2/3 of the data for training and the remainder for test in internal validation. The best performance was achieved using a linear support vector machine (SVM) model on the combined vectors derived from term frequency-inverse document frequency (TF-IDF) and Word2Vec, resulting in an accuracy of 95.0% and an F1-score of 95.0%. The final SVM model constructed from all 14,203 publications was tested on independent datasets, resulting in accuracies of 92.5%, 96.3%, and 98.3%, and F1-scores of 93.5%, 86.1%, and 75.6% for three test sets (T1-T3). Furthermore, the SVM model was tested on four external validation sets (V1-V4), resulting in accuracies of 92.0%, 96.2%, 98.3%, and 93.1%, and F1-scores of 92.4%, 82.9%, 75.0%, and 93.3%. [ABSTRACT FROM AUTHOR]

Published
2023
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45. Physiology of Glymphatic Solute Transport and Waste Clearance from the Brain.

Author

Zhao, Lucy, Tannenbaum, Allen, Bakker, Erik N. T. P., and Benveniste, Helene

Subjects
*CENTRAL nervous system, *PHYSIOLOGY, *CEREBROSPINAL fluid, *LABORATORY animals, *ANIMAL models in research
Abstract

This review focuses on the physiology of glymphatic solute transport and waste clearance, using evidence from experimental animal models as well as from human studies. Specific topics addressed include the biophysical characteristics of fluid and solute transport in the central nervous system, glymphaticlymphatic coupling, as well as the role of cerebrospinal fluid movement for brain waste clearance. We also discuss the current understanding of mechanisms underlying increased waste clearance during sleep. [ABSTRACT FROM AUTHOR]

Published
2022
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46. Changes in the geometry and robustness of diffusion tensor imaging networks: Secondary analysis from a randomized controlled trial of young autistic children receiving an umbilical cord blood infusion.

Author

Simhal, Anish K., Carpenter, Kimberly L. H., Kurtzberg, Joanne, Song, Allen, Tannenbaum, Allen, Zhang, Lijia, Sapiro, Guillermo, and Dawson, Geraldine

Subjects
DIFFUSION tensor imaging, CORD blood, AUTISTIC children, RANDOMIZED controlled trials, SECONDARY analysis
Abstract

Diffusion tensor imaging (DTI) has been used as an outcome measure in clinical trials for several psychiatric disorders but has rarely been explored in autism clinical trials. This is despite a large body of research suggesting altered white matter structure in autistic individuals. The current study is a secondary analysis of changes in white matter connectivity from a doubleblind placebo-control trial of a single intravenous cord blood infusion in 2-7-year-old autistic children (1). Both clinical assessments and DTI were collected at baseline and 6 months after infusion. This study used two measures of white matter connectivity: change in node-to-node connectivity as measured through DTI streamlines and a novel measure of feedback network connectivity, Ollivier-Ricci curvature (ORC). ORC is a network measure which considers both local and global connectivity to assess the robustness of any given pathway. Using both the streamline and ORC analyses, we found reorganization of white matter pathways in predominantly frontal and temporal brain networks in autistic children who received umbilical cord blood treatment versus those who received a placebo. By looking at changes in network robustness, this study examined not only the direct, physical changes in connectivity, but changes with respect to the whole brain network. Together, these results suggest the use of DTI and ORC should be further explored as a potential biomarker in future autism clinical trials. These results, however, should not be interpreted as evidence for the efficacy of cord blood for improving clinical outcomes in autism. This paper presents a secondary analysis using data from a clinical trial that was prospectively registered with ClinicalTrials.gov (NCT02847182). [ABSTRACT FROM AUTHOR]

Published
2022
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