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Artificial intelligence

Applying Deutsch’s concept of good explanations to artificial intelligence and neuroscience - An initial exploration
D. C. Elton. Cognitive Systems Research. 67 pgs 9–17. (2021) [link] [arXiv] [.bib]

Common Pitfalls When Explaining AI and Why Mechanistic Explanation Is a Hard Problem
D. C. Elton. Chapter in Proceedings of Sixth International Congress on Information and Communication Technology. pgs 401–408. (2021) [link] [.bib][pdf]

Self-explaining AI as an Alternative to Interpretable AI
D. C. Elton. Chapter in Proceedings of the 13th Annual Conference on Artificial General Intelligence (AGI-2020). pgs 95-106. (2020) [link] [arXiv] [.bib]

Machine learning for medical imaging

Lymph node detection in T2 MRI with transformers
Tejas S. Mathai, S. Lee, D. C. Elton, Tommy Shen, R. M. Summers. To appear in proceedings of SPIE Medical Imaging 2022: Computer-Aided Diagnosis. (2022) [.bib]

Cardiovascular disease and all-cause mortality risk prediction from abdominal CT using deep learning
D. C. Elton, A. Chen, P. J. Pickhardt, R. M. Summers. To appear in proceedings of SPIE Medical Imaging 2022: Computer-Aided Diagnosis. (2021) [medRxiv] [.bib]

Learning Structure from Visual Semantic Features and Radiology Ontology for Lymph Node Classification on MRI
Y. Zhu, Shuai Wang, Q. Chen, S. Lee, T. Shen, D. C. Elton, Z. Lu, R. M. Summers. Chapter in Machine Learning in Medical Imaging. pgs 101–109. (2021) [link] [.bib][pdf]

Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value
P. J. Pickhardt, P. M. Graffy, A. A. Perez, Meghan G. Lubner, D. C. Elton, R. M. Summers. RadioGraphics. 41 (2) pgs 524–542. (2021) [link] [.bib][pdf]

Detection of Lymph Nodes in T2 MRI Using Neural Network Ensembles
Tejas Sudharshan Mathai, S. Lee, D. C. Elton, Thomas C. Shen, Yifan Peng, Z. Lu, R. M. Summers. Chapter in Machine Learning in Medical Imaging. pgs 682–691. (2021) [link] [.bib][pdf]

Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1204 Healthy Adults Using Unenhanced CT as a Reference Standard
P. J. Pickhardt, Glen M. Blake, P. M. Graffy, V. Sandfort, D. C. Elton, A. A. Perez, R. M. Summers. American Journal of Roentgenology. 217 (2) pgs 359–367. (2021) [link] [.bib][pdf]

Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection
Y. Zhu, D. C. Elton, S. Lee, P. J. Pickhardt, R. M. Summers. Proceedings of the 2020 Medical Imaging with Deep Learning (MIDL) Conference. (2020) [arXiv] [.bib][pdf]

Cross-domain Medical Image Translation by Shared Latent Gaussian Mixture Model
Y. Zhu, Y. Tang, Y. Tang, D. C. Elton, S. Lee, P. J. Pickhardt, R. M. Summers. Chapter in Medical Image Computing and Computer Assisted Intervention (\MICCAI) 2020. pgs 379–389. (2020) [link] [.bib][pdf]

Deep Small Bowel Segmentation with Cylindrical Topological Constraints
S. Y. Shin, S. Lee, D. C. Elton, J. L. Gulley, R. M. Summers. Chapter in Medical Image Computing and Computer Assisted Intervention \textendash MICCAI 2020. pgs 207–215. (2020) [link] [.bib][pdf]

Automatic recognition of abdominal lymph nodes from clinical text
Y. Peng, S. Lee, D. C. Elton, T. Shen, Y. Tang, Q. Chenand S. Wang, Y. Zhu, R. M. Summers, Z. Lu. Chapter in Proceedings of the 3rd Clinical Natural Language Processing Workshop. pgs 101–110. (2020) [link] [.bib][pdf]

Atherosclerotic Plaque Burden on Abdominal CT: Automated Assessment With Deep Learning on Noncontrast and Contrast-enhanced Scans
R. M. Summers, D. C. Elton, S. Lee, Y. Zhu, J. Liu, M. Bagheri, V. Sandfort, Peter C. Grayson, Nehal N. Mehta, P. A. Pinto, W. Marston Linehan, A. A. Perez, P. M. Graffy, Stacy D. O’Connor, P. J. Pickhardt. Academic Radiology. (2020) [link] [.bib][pdf]

Fully automated CT imaging biomarkers of bone, muscle, and fat: correcting for the effect of intravenous contrast
A. A. Perez, P. J. Pickhardt, D. C. Elton, V. Sandfort, R. M. Summers. Abdominal Radiology. 46 (3) pgs 1229–1235. (2020) [link] [.bib][pdf]

Accurately identifying vertebral levels in large datasets
D. C. Elton, V. Sandfort, P. J. Pickhardt, R. M. Summers. Chapter in Medical Imaging 2020: Computer-Aided Diagnosis. (2020) [link] [arXiv] [.bib][pdf]

Machine learning for molecular design

Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning
Z. Boukouvalas, M. Puerto, D. C. Elton, P. W. Chung, M. D. Fuge. * Proceedings of the 28th European Signal Processing Conference (EUSIPCO 2020)*. (2018) [arXiv] [.bib][pdf]

Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora
D. C. Elton, D. Turakhia, N. Reddy, Z. Boukouvalas, R. M. Doherty, M. D. Fuge, P. W. Chung. Proceedings of the 22nd International Seminar on New Trends in Research of Energetic Materials. (2019) [arXiv] [.bib]

Deep learning for molecular design - a review of the state of the art
D. C. Elton, Z. Boukouvalas, M. D. Fuge, P. W. Chung. Molecular Systems Design & Engineering. 4 (4) pgs 828–849. (2019) [link] [arXiv] [.bib][pdf]

Applying machine learning techniques to predict the properties of energetic materials
D. C. Elton, Z. Boukouvalas, M. S. Butrico, M. D. Fuge, P. W. Chung. Scientific Reports. 8 (1) (2018) [link] [arXiv] [.bib][pdf]

Machine Learning of Energetic Material Properties
B. C. Barnes, D. C. Elton, Z. Boukouvalas, D. E. Taylor, W. D. Mattson, M. D. Fuge, P. W. Chung. Proceedings of the 22nd International Seminar on New Trends in Research of Energetic Materials. (2018) [arXiv] [.bib]

Physics of detonation

Phonon Lifetimes and Thermal Conductivity of the Molecular Crystal α-RDX
G. Kumar, F. G. Van Gessel, D. C. Elton, P. W. Chung. MRS Advances. 4 (40) pgs 2191–2199. (2019) [link] [.bib][pdf]

A Phonon Boltzmann Study of Microscale Thermal Transport in α-RDX Cook-Off
Francis G. VanGessel, G. Kumar, D. C. Elton, P. W. Chung. Proceedings of the 22nd International Seminar on New Trends in Research of Energetic Materials. (2018) [arXiv] [.bib]

Physics of water

Pathological Water Science - Four Examples and What They Have in Common
D. C. Elton, P. D. Spencer. Chapter in Biologically-Inspired Systems. pgs 155–169. (2021) [link] [arXiv] [.bib][pdf]

Exclusion Zone Phenomena in Water - A Critical Review of Experimental Findings and Theories
D. C. Elton, P. D. Spencer, J. D. Riches, E. D. Williams. International Journal of Molecular Sciences. 21 (14) pgs 5041. (2020) [link] [arXiv] [.bib]

Using a monomer potential energy surface to perform approximate path integral molecular dynamics simulation of ab initio water at near-zero added cost
D. C. Elton, M. Fritz, Marivi Fern'andez-Serra. Physical Chemistry Chemical Physics. 21 (1) pgs 409–417. (2019) [link] [arXiv] [.bib][pdf]

The origin of the Debye relaxation in liquid water and fitting the high frequency excess response
D. C. Elton. Physical Chemistry Chemical Physics. 19 (28) pgs 18739–18749. (2017) [link] [arXiv] [.bib][pdf]

The hydrogen-bond network of water supports propagating optical phonon-like modes
D. C. Elton, Marivi Fern'andez-Serra. Nature Communications. 7 (1) (2016) [link] [arXiv] [.bib][pdf]

Polar nanoregions in water: A study of the dielectric properties of TIP4P/2005, TIP4P/2005f and TTM3F
D. C. Elton, M.-V. Fern'andez-Serra. The Journal of Chemical Physics. 140 (12) pgs 124504. (2014) [link] [arXiv] [.bib][pdf]

Other

Using Third-Order Moments of Fluctuations in V and B to Determine Turbulent Heating Rates in the Solar Wind
M. A. Forman, C. W. Smith, B. J. Vasquez, B. T. MacBride, J. E. Stawarz, J. J. Podesta, D. C. Elton, U. Y. Malecot, Y. Gagne, M. Maksimovic, K. Issautier, N. Meyer-Vernet, M. Moncuquet, F. Pantellini. Chapter in AIP Conference Proceedings 1216, 12th International Solar Wind Conference, 176 (2010). (2010) [link] [.bib][pdf]

Accurate estimation of third-order moments from turbulence measurements
J. J. Podesta, M. A. Forman, C. W. Smith, D. C. Elton, Y. Mal'ecot, Y. Gagne. Nonlinear Processes in Geophysics. 16 (1) pgs 99–110. (2009) [link] [.bib][pdf]

Ph.D. Thesis

atom in a clathrate-like cage

Understanding the Dielectric Properties of Water (11 Mb PDF)

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