Alyson Wilson

Hollis, A. N., Moore, T. A., Wilson, A. G., & Clark, N. J. (2024). From FMECA to Decision: A Fully Bayesian Reliability Process. MILITARY OPERATIONS RESEARCH, 29(1). https://doi.org/10.5711/1082598329145

Nuclear War, C., Mathematical Sciences, B., Nuclear, International Security, C., Engineering, D., Earth, D., … Sciences, E. (2024). Risk Analysis Methods for Nuclear War and Nuclear Terrorism. https://doi.org/10.17226/27745

Hameed, K., Johnston, R., Younce, B., Tang, M., & Wilson, A. (2023). Motif-Based Exploratory Data Analysis for State-Backed Platform Manipulation on Twitter. Proceedings of the International AAAI Conference on Web and Social Media. https://doi.org/10.1609/icwsm.v17i1.22148

Nuclear War, C., Mathematical Sciences, B., Nuclear, International Security, C., Engineering, D., Earth, D., … Sciences, E. (2023). Risk Analysis Methods for Nuclear War and Nuclear Terrorism. https://doi.org/10.17226/26609

Nuclear War, C., Mathematical Sciences, B., Nuclear, International Security, C., Engineering, D., Earth, D., … Sciences, E. (2023). Risk Analysis Methods for Nuclear War and Nuclear Terrorism. https://doi.org/10.17226/27393

Bakerman, J., Pazdernik, K., Korkmaz, G., & Wilson, A. G. (2022). Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest. INTERNATIONAL JOURNAL OF FORECASTING, 38(2), 648–661. https://doi.org/10.1016/j.ijforecast.2021.07.003

Emerging Hazards in Commercial Aviation-Report 1: Initial Assessment of Safety Data and Analysis Processes. (2022). In Transportation Research Board. https://doi.org/10.17226/26673

Wendelberger, L. J., Gray, J. M., Wilson, A. G., Houborg, R., & Reich, B. J. (2022). Multiresolution Broad Area Search: Monitoring Spatial Characteristics of Gapless Remote Sensing Data. Journal of Data Science. https://doi.org/10.6339/22-JDS1072

Standards, P., NIST Technical Programs, C., Board, L. A., Engineering, D., & Sciences, E. (2021). An Assessment of Selected Divisions of the Information Technology Laboratory at the National Institute of Standards and Technology. In National Academies Press. https://doi.org/10.17226/26354

Data Use, C., Mathematical Sciences, B., Applied, C., Board, A. F. S., Science, C., Higher Education, B., … Sciences, E. (2021). Empowering the Defense Acquisition Workforce to Improve Mission Outcomes Using Data Science. In National Academies Press. https://doi.org/10.17226/25979

Wendelberger, L. J., Reich, B. J., & Wilson, A. G. (2021). Multi-model penalized regression. STATISTICAL ANALYSIS AND DATA MINING, 14(6), 698–722. https://doi.org/10.1002/sam.11496

Cahoon, J., Sanborn, K., & Wilson, A. (2021). Practical reliability growth modeling. Quality and Reliability Engineering International. https://doi.org/10.1002/qre.2822

Hollis, A. N., Smith, R. C., & Wilson, A. G. (2021). SURROGATE BASED MUTUAL INFORMATION APPROXIMATION AND OPTIMIZATION FOR URBAN SOURCE LOCALIZATION. INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 11(5), 39–55. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2021034400

Chakraborty, A., Lahiri, S. N., & Wilson, A. (2020). A STATISTICAL ANALYSIS OF NOISY CROWDSOURCED WEATHER DATA. ANNALS OF APPLIED STATISTICS, 14(1), 116–142. https://doi.org/10.1214/19-AOAS1290

Algorithms in Diffraction Profile Analysis. (2020). In Handbook on Big Data and Machine Learning in the Physical Sciences. https://doi.org/doi.org/10.1142/11389

Broughton, R., O'Donnell, S., Gabilondo, E., Chung, C.-C., Maggard, P., Wilson, A., … Jones, J. (2020). Bayesian refinement of full profile diffraction patterns for uncertainty quantification. Acta Crystallographica Section A Foundations and Advances. https://doi.org/10.1107/s0108767320099560

Lee, J., Rathsam, J., & Wilson, A. (2020). Bayesian statistical models for community annoyance survey data. The Journal of the Acoustical Society of America. https://doi.org/10.1121/10.0001021

Mathematical Sciences, B., Engineering, D., & Sciences, E. (2020). Improving Defense Acquisition Workforce Capability in Data Use. In National Academies Press. https://doi.org/10.17226/25922

Durodoye, R., Jr., Gumpertz, M., Wilson, A., Griffith, E., & Ahmad, S. (2020). Tenure and Promotion Outcomes at Four Large Land Grant Universities: Examining the Role of Gender, Race, and Academic Discipline. RESEARCH IN HIGHER EDUCATION, 61(5), 628–651. https://doi.org/10.1007/s11162-019-09573-9

Gilman, J. F., Fronczyk, K. M., & Wilson, A. G. (2019). Bayesian modeling and test planning for multiphase reliability assessment. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 35(3), 750–760. https://doi.org/10.1002/qre.2406

Tian, Y., Bondell, H. D., & Wilson, A. (2019). Bayesian variable selection for logistic regression. STATISTICAL ANALYSIS AND DATA MINING, 12(5), 378–393. https://doi.org/10.1002/sam.11428

Typhina, E., & Wilson, A. (2019). Discussion on “Effective interdisciplinary collaboration between statisticians and other subject matter experts.” Quality Engineering, 31(1), 192–194. https://doi.org/10.1080/08982112.2018.1539233

Wilson, A., Schmidt, M., Schmidt, L., & Winter, B. (2019). Immersive Collaboration on Data Science for Intelligence Analysis. Harvard Data Science Review. https://doi.org/10.1162/99608f92.4a9eef8d

Gasior, K., Wagner, N. J., Cores, J., Caspar, R., Wilson, A., Bhattacharya, S., & Hauck, M. L. (2019). The role of cellular contact and TGF-beta signaling in the activation of the epithelial mesenchymal transition (EMT). CELL ADHESION & MIGRATION, 13(1), 63–75. https://doi.org/10.1080/19336918.2018.1526597

Jones, J. L., Broughton, R., Iamsasri, T., Fancher, C. M., Wilson, A. G., Reich, B., & Smith, R. C. (2019). The use of Bayesian inference in the characterization of materials and thin films. ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES, Vol. 75, pp. A211–A211. https://doi.org/10.1107/S0108767319097940

Paterson, A. R., Reich, B. J., Smith, R. C., Wilson, A. G., & Jones, J. L. (2018). Bayesian Approaches to Uncertainty Quantification and Structure Refinement from X-Ray Diffraction. In Materials Discovery and Design (pp. 81–102). https://doi.org/10.1007/978-3-319-99465-9_4

Rendon, H., Wilson, A., & Stegall, J. (2018). Is it "Fake News'? Intelligence Community expertise and news dissemination as measurements for media reliability. INTELLIGENCE AND NATIONAL SECURITY, 33(7), 1040–1052. https://doi.org/10.1080/02684527.2018.1507381

Behavioral, C., Behavioral, D., & Sciences, E. (2018). Learning from the Science of Cognition and Perception for Decision Making. In National Academies Press. https://doi.org/10.17226/25118

Zoh, R., Wilson, A., Vander Wiel, S., & Lawrence, E. (2018). The negative log-gamma prior distribution for Bayesian assessment of system reliability. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY, 232(3), 308–319. https://doi.org/10.1177/1748006x17692154

Bakerman, J., Pazdernik, K., Wilson, A., Fairchild, G., & Bahran, R. (2018). Twitter Geolocation. ACM Transactions on Knowledge Discovery from Data. https://doi.org/10.1145/3178112

Bakerman, J., Pazdernik, K., Wilson, A., Fairchild, G., & Bahran, R. (2018). Twitter geolocation: A hybrid approach. ACM Transactions on Knowledge Discovery from Data, 12(3).

 Hierarchical Bayesian Modeling of Atomic Structural Disorder. (2017). Proceedings of the International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering.

Iamsasri, T., Guerrier, J., Esteves, G., Fancher, C. M., Wilson, A. G., Smith, R. C., … Jones, J. L. (2017). A Bayesian approach to modeling diffraction profiles and application to ferroelectric materials. Journal of Applied Crystallography, 50(1), 211–220. https://doi.org/10.1107/s1600576716020057

Weaver, B. P., Hamada, M. S., Wilson, A. G., & Bakerman, J. E. (2017). Bayesian assurance tests for degradation data. Quality and Reliability Engineering International, 33(8), 2699–2709. https://doi.org/10.1002/QRE.2228

Wilson, A. G., & Fronczyk, K. M. (2017). Bayesian reliability: Combining information. Quality Engineering, 29(1), 119–129.

Wilson, A. G., & Fronczyk, K. M. (2017). National Security Risk Analysis. In Wiley StatsRef: Statistics Reference Online. https://doi.org/10.1002/9781118445112.stat07971

Gumpertz, M., Durodoye, R., Griffith, E., & Wilson, A. (2017). Retention and promotion of women and underrepresented minority faculty in science and engineering at four large land grant institutions. PLOS ONE. https://doi.org/10.1371/journal.pone.0187285

Zhang, X., & Wilson, A. (2017). System Reliability and Component Importance Under Dependence: A Copula Approach. TECHNOMETRICS, 59(2), 215–224. https://doi.org/10.1080/00401706.2016.1142907

A Bayesian approach to evaluation of operational testing of land warfare systems. (2016, January). Military Operations Research. https://doi.org/10.5711/1082598321423

Wilson, A. G., & Fronczyk, K. M. (2016). Bayesian Reliability: Combining Information. Quality Engineering, 8, 0–0. https://doi.org/10.1080/08982112.2016.1211889

Lenhardt, W. C., Conway, M., Scott, E., Blanton, B., Krishnamurthy, A., Hadzikadic, M., … Wilson, A. (2016). Cross-institutional research cyberinfrastructure for data intensive science. 2016 ieee high performance extreme computing conference (hpec). https://doi.org/10.1109/hpec.2016.7761597

Graham, H. T., Rotroff, D. M., Marvel, S. W., Buse, J. B., Havener, T. M., Wilson, A. G., … Motsinger-Reif, A. A. (2016). Incorporating Concomitant Medications into Genome-Wide Analyses for the Study of Complex Disease and Drug Response. Frontiers in Genetics, 7. https://doi.org/10.3389/fgene.2016.00138

Fancher, C. M., Han, Z., Levin, I., Page, K., Reich, B. J., Smith, R. C., … Jones, J. L. (2016). Use of Bayesian Inference in Crystallographic Structure Refinement via Full Diffraction Profile Analysis. Scientific Reports, 6(1), 31625. https://doi.org/10.1038/srep31625

Stracuzzi, D. J., Brost, R. C., Phillips, C. A., Robinson, D. G., Wilson, A. G., & Woodbridge, D. M.-K. (2015). Computing quality scores and uncertainty for approximate pattern matching in geospatial semantic graphs. STATISTICAL ANALYSIS AND DATA MINING, Vol. 8, pp. 340–352. https://doi.org/10.1002/sam.11294

Steiner, S., Dickinson, R. M., Freeman, L. J., Simpson, B. A., & Wilson, A. G. (2015). Statistical Methods for Combining Information: Stryker Family of Vehicles Reliability Case Study. Journal of Quality Technology, 47(4), 400–415. https://doi.org/10.1080/00224065.2015.11918142

Berry, J. W., Fostvedt, L. A., Nordman, D. J., Phillips, C. A., Seshadhri, C., & Wilson, A. G. (2015). WHY DO SIMPLE ALGORITHMS FOR TRIANGLE ENUMERATION WORK IN THE REAL WORLD? INTERNET MATHEMATICS, 11(6), 555–571. https://doi.org/10.1080/15427951.2015.1037030

Casleton, E., Beyler, A., Genschel, U., & Wilson, A. (2014). A Pilot Study Teaching Metrology in an Introductory Statistics Course. Journal of Statistics Education, 22(3). https://doi.org/10.1080/10691898.2014.11889710

Hamada, M. S., Wilson, A. G., Weaver, B. P., Griffiths, R. W., & Martz, H. F. (2014). Bayesian Binomial Assurance Tests for System Reliability Using Component Data. JOURNAL OF QUALITY TECHNOLOGY, 46(1), 24–32. https://doi.org/10.1080/00224065.2014.11917952

Complex Operational Decision Making in Networked Systems of Humans and Machines. (2014). In National Academies Press. https://doi.org/10.17226/18844

Reese, C. S., & Wilson, A. G. (2014). Discussion of 'Methods for planning repeated measures accelerated degradation tests'. APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 30(6), 674–676. https://doi.org/10.1002/asmb.2090

Berry, J. W., Leung, V. J., Phillips, C. A., Pinar, A., Robinson, D. G., Berger-Wolf, T., … Wilson, A. G. (2014). Statistically significant relational data mining : https://doi.org/10.2172/1204082

Berry, J. W., Fostvedt, L. K., Nordman, D. J., Phillips, C. A., Seshadhri, C., & Wilson, A. G. (2014). Why do simple algorithms for triangle enumeration work in the real world? ITCS 2014 - Proceedings of the 2014 Conference on Innovations in Theoretical Computer Science, 225–234. https://doi.org/10.1145/2554797.2554819

Wendelberger, J., Wilson, A., Stinnett, S., & Gaydos, B. (2014). Working in Interdisciplinary Teams. CHANCE. https://doi.org/10.1080/09332480.2014.988955

Guo, J., & Wilson, A. G. (2013). Bayesian Methods for Estimating System Reliability Using Heterogeneous Multilevel Information. TECHNOMETRICS, 55(4), 461–472. https://doi.org/10.1080/00401706.2013.804441

Guo, J., Nordman, D. J., & Wilson, A. (2013). Bayesian nonparametric models for community detection. Technometrics, 55(4), 390–402. https://doi.org/10.1080/00401706.2013.804438

Weaver, B. P., Hamada, M. S., Vardeman, S. B., & Wilson, A. G. (2012). A Bayesian approach to the analysis of gauge R&R data. Quality Engineering, 24(4), 486–500. https://doi.org/10.1080/08982112.2012.702381

Assessing the Reliability of Complex Models. (2012). In National Academies Press. https://doi.org/10.17226/13395

Industrial Methods for the Effective Development and Testing of Defense Systems. (2012). In National Academies Press. https://doi.org/10.17226/13291

Anderson-Cook, C. M., Lu, L., Clark, G., Dehart, S. P., Hoerl, R., Jones, B., … Wilson, A. G. (2012). Statistical engineering-forming the foundations. Quality Engineering, 24(2), 110–132. https://doi.org/10.1080/08982112.2012.641150

Anderson-Cook, C. M., Lu, L., Clark, G., Dehart, S. P., Hoerl, R., Jones, B., … Wilson, A. G. (2012). Statistical engineering-roles for statisticians and the path forward. Quality Engineering, 24(2), 133–152. https://doi.org/10.1080/08982112.2012.641151

Testing of Body Armor Materials. (2012). In National Academies Press. https://doi.org/10.17226/13390

Reese, C. S., Wilson, A. G., Guo, J., Hamada, M. S., & Johnson, V. E. (2011). A Bayesian Model for Integrating Multiple Sources of Lifetime Information in System-Reliability Assessments. Journal of Quality Technology, 43(2), 127–141. https://doi.org/10.1080/00224065.2011.11917851

Wilson, A. G., Anderson-Cook, C. M., & Huzurbazar, A. V. (2011). A case study for quantifying system reliability and uncertainty. Reliability Engineering and System Safety, 96(9), 1076–1084. https://doi.org/10.1016/j.ress.2010.09.012

Wiel, S. V., Graves, T., Wilson, A., & Reese, S. (2011). A random onset model for degradation of high-reliability systems. Technometrics, 53(2), 163–172. https://doi.org/10.1198/TECH.2011.09119

Hamada, M. S., Huzurbazar, A. V., Vander Wiel, S., & Wilson, A. G. (2011). Assessing the risks of sampling rates for surveilling a population. Quality Engineering, 23(3), 242–252. https://doi.org/10.1080/08982112.2011.575747

Lu, L., Anderson-Cook, C. M., & Wilson, A. G. (2011). Choosing a consumption strategy for a population of units based on reliability. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 225(4), 407–423. https://doi.org/10.1177/1748006X11392287

Anderson-Cook, C. M., Crowder, S., Huzurbazar, A. V., Lorio, J., Ringland, J., & Wilson, A. G. (2011). Quantifying reliability uncertainty from catastrophic and margin defects: A proof of concept. Reliability Engineering and System Safety, 96(9), 1063–1075. https://doi.org/10.1016/j.ress.2010.10.006

Wilson, A. G., & Anderson-Cook, C. M. (2010). Comment. Technometrics, 52(4), 397–400. https://doi.org/10.1198/TECH.2010.09178

Kegelmeyer, W. P., Jr. (2010). Network discovery, characterization, and prediction : a grand challenge LDRD final report. https://doi.org/10.2172/1011623

Testing of Body Armor Materials for Use by the U.S. Army--Phase II. (2010). In National Academies Press. https://doi.org/10.17226/12885

Phase I Report on Review of the Testing of Body Armor Materials for Use by the U.S. Army. (2009). In National Academies Press. https://doi.org/10.17226/12837

Singpurwalla, N. D., & Wilson, A. G. (2009). Probability, chance and the probability of chance. IIE Transactions (Institute of Industrial Engineers), 41(1), 12–22. https://doi.org/10.1080/07408170802322630

Diegert, K. V., Dvorack, M. A., Ringland, J. T., Mundt, M. J., Huzurbazar, A. ; Lorio, J. F., … Zurn, R. M. (2009). Quantifying reliability uncertainty : a proof of concept. https://doi.org/10.2172/970305

Parnell, G. S., Borio, L. L., Cox, L. A., Brown, G. G., Pollock, S., & Wilson, A. G. (2009). Response to Ezell and von Winterfeldt. Biosecurity and Bioterrorism, 7(1), 111–112. https://doi.org/10.1089/bsp.2009.0927

Wilson, A. G., Huzurbazar, A. V., & Sentz, K. (2009). The Imprecise Dirichlet Model for Multilevel System Reliability. Journal of Statistical Theory and Practice, 3(1), 211–223. https://doi.org/10.1080/15598608.2009.10411921

Hamada, M. S., Wilson, A. G., Reese, C. S., & Martz, H. F. (2008). Bayesian Reliability. In Springer New York. https://doi.org/10.1007/978-0-387-77950-8

Department of Homeland Security Bioterrorism Risk Assessment. (2008). In National Academies Press. https://doi.org/10.17226/12206

Anderson-Cook, C. M., Graves, T., Hengartner, N., Klamann, R., Wiedlea, A. C. K., Wilson, A. G., … Lopez, G. (2008). Reliability Modeling using Both System Test and Quality Assurance Data. Military Operations Research. https://doi.org/10.5711/morj.13.3.5

Parnell, G. S., Borio, L. L., Brown, G. G., Banks, D., & Wilson, A. G. (2008). Scientists urge DHS to improve bioterrorism risk assessment. Biosecurity and Bioterrorism, 6(4), 353–356. https://doi.org/10.1089/bsp.2008.0930

Anderson-Cook, C. M., Graves, T., Hamada, M., Hengartner, N., Johnson, V. E., Reese, C. S., & Wilson, A. G. (2007). Bayesian Stockpile Reliability Methodology for Complex Systems. Military Operations Research. https://doi.org/10.5711/morj.12.2.25

Wilson, A. G., & Huzurbazar, A. V. (2007). Bayesian networks for multilevel system reliability. Reliability Engineering and System Safety, 92(10), 1413–1420. https://doi.org/10.1016/j.ress.2006.09.003

Wilson, A. G. (2007). Hierarchical Markov Chain Monte Carlo (MCMC) for Bayesian System Reliability. In Encyclopedia of Statistics in Quality and Reliability. https://doi.org/10.1002/9780470061572.eqr094

Wilson, A. G., McNamara, L. A., & Wilson, G. D. (2007). Information integration for complex systems. Reliability Engineering and System Safety, 92(1), 121–130. https://doi.org/10.1016/j.ress.2006.07.003

Wilson, A. G., Graves, T. L., Hamada, M. S., & Reese, C. S. (2006). Advances in data combination, analysis and collection for system reliability assessment. Statistical Science, 21(4), 514–531. https://doi.org/10.1214/088342306000000439

Keller-McNulty, S., Wilson, A., & Anderson-Cook, C. (2006). Reliability. Statistical Science, 21(4). https://doi.org/10.1214/088342306000000664

Wilson, A. G., Wilson, G. D., & Olwell, D. H. (2006). Statistical methods in counterterrorism: Game theory, modeling, syndromic surveillance, and biometric authentication. In Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication (pp. 1–292). https://doi.org/10.1007/0-387-35209-0

Sentz, K., & Wilson, A. (2005). Fault tree uncertainty quantification using probabilities and belief structures on basic and non-basic events. Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, 2005, 65–68. https://doi.org/10.1109/NAFIPS.2005.1548509

Wilson, A., Limnios, N., Keller-McNulty, S., & Armijo, Y. (2005). Modern Statistical and Mathematical Methods in Reliability. In Series on Quality, Reliability and Engineering Statistics. https://doi.org/10.1142/5844

Keller-McNulty, S., Wilson, A. G., & Wilson, G. (2005). The Impact of Technology on the Scientific Method. CHANCE. https://doi.org/10.1080/09332480.2005.10722744

Hamada, M., Martz, H. F., Reese, C. S., Graves, T., Johnson, V., & Wilson, A. G. (2004). A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation. Reliability Engineering and System Safety, 86(3), 297–305. https://doi.org/10.1016/j.ress.2004.02.001

Wilson, A., Hamada, M., & Xu, M. (2004). Assessing Production Quality with Nonstandard Measurement Errors. Journal of Quality Technology. https://doi.org/10.1080/00224065.2004.11980265

Improved Operational Testing and Evaluation and Methods of Combining Test Information for the Stryker Family of Vehicles and Related Army Systems. (2004). In National Academies Press. https://doi.org/10.17226/10871

Integrated Analysis of Computational and Physical Experimental Lifetime Data. (2004). In Mathematical Reliability: An Expository Perspective. https://doi.org/10.1007/978-1-4419-9021-1

Reese, C. S., Wilson, A. G., Hamada, M., Martz, H. F., & Ryan, K. J. (2004). Integrated Analysis of Computer and Physical Experiments. Technometrics. https://doi.org/10.1198/004017004000000211

Improved Operational Testing and Evaluation. (2003). In National Academies Press. https://doi.org/10.17226/10710

Reliability for the 21st Century. (2003). In Mathematical and Statistical Methods in Reliability. https://doi.org/doi.org/10.1142/5248

Test Design and Evaluation for the Interim Armored Vehicle: Letter Report. (2002). In National Academies Press. https://doi.org/10.17226/10529

Hamada, M., Martz, H. F., Reese, C. S., & Wilson, A. G. (2001). Finding near-optimal Bayesian experimental designs via Genetic algorithms. American Statistician, 55(3), 175–181. https://doi.org/10.1198/000313001317098121

L, C. H. A. N. E. Y. E. D. W. A. R. D., S, F. R. I. T. S. C. H. D. A. N. I. E. L., M, P. I. Z. E. R. S. T. E. P. H. E. N., VALEN, J. O. H. N. S. O. N., & G, W. I. L. S. O. N. A. L. Y. S. O. N. (1999). Image object matching using core analysis and deformable shape loci. Retrieved from https://www.lens.org/161-652-391-335-889

Wilson, A. G., & Johnson, V. E. (1996). Models for Shape Deformation. In Bayesian Statistics 5. https://doi.org/10.1093/oso/9780198523567.003.0061

Knebel, A. R., Janson-Bjerklie, S. L., Malley, J. D., Wilson, A. G., & Marini, J. J. (1994). Comparison of breathing comfort during weaning with two ventilatory modes. American Journal of Respiratory and Critical Care Medicine. https://doi.org/10.1164/ajrccm.149.1.8111572

Wilson, A. G., & Johnson, V. E. (1994). Priors on scale-space templates. SPIE Proceedings. https://doi.org/10.1117/12.179247