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SCIInstitute · Apr 10, 2023 · f57e499 · f57e499
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diff --git a/docs/index.rst b/docs/index.rst
@@ -13,10 +13,10 @@ Welcome to UncertainSCI's documentation!
 About UncertainSCI
 ===================
 
-UncertainSCI is a Python-based toolkit that harnesses modern techniques to estimate model and parametric uncertainty, with a particular emphasis on needs for biomedical simulations and applications. This toolkit enables non-intrusive integration of these techniques with well-established biomedical simulation software.
+UncertainSCI :cite:p:`JDT:Nar2022` is a Python-based toolkit that harnesses modern techniques to estimate model and parametric uncertainty, with a particular emphasis on needs for biomedical simulations and applications. This toolkit enables non-intrusive integration of these techniques with well-established biomedical simulation software.
 
 
-Currently implemented in UncertainSCI is Polynomial Chaos Expansion (PCE) with a number of input distributions.  For more information about these techniques, see: :cite:p:`JDT:Bur2020,narayan_computation_2018,guo_weighted_2018,cohen_optimal_2017`
+Currently implemented in UncertainSCI is Polynomial Chaos Expansion (PCE) with a number of input distributions.  For more information about these techniques, see: :cite:p:`JDT:Bur2020,narayan_computation_2018,guo_weighted_2018,cohen_optimal_2017`.  For studies using UncertainSCI, see: :cite:p:`JDT:DT:Ber2021,JDT:Rup2020,JDT:Rup2021,JDT:Tat2021a,JDT:Tat2021c,JDT:Tat2022`
 
 
 .. toctree::

diff --git a/docs/references.bib b/docs/references.bib
@@ -7,19 +7,128 @@ @techreport{gupta1983
 	year = {1983},
 }
 
-@article{JDT:Bur2020,
-author = {Burk, Kyle M. and Narayan, Akil and Orr, Joseph A.},
-title = {Efficient sampling for polynomial chaos-based uncertainty quantification and sensitivity analysis using weighted approximate Fekete points},
-journal = {International Journal for Numerical Methods in Biomedical Engineering},
-volume = {36},
-number = {11},
-pages = {e3395},
-keywords = {approximate Fekete points, cardiovascular modeling, oxyhemoglobin dissociation, polynomial chaos expansion, sensitivity analysis, uncertainty quantification},
-doi = {https://doi.org/10.1002/cnm.3395},
-url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cnm.3395},
-year = {2020}
+@Article{JDT:Nar2022,
+  title =        "Uncertain{SCI}: Uncertainty Quantification for
+                 Computational Models in Biomedicine and
+                 Bioengineering",
+  author =       "Akil Narayan and Zexin Liu and Jake Bergquist and
+                 Chantel Charlebois and Sumientra Rampersad and Lindsay
+                 Rupp and Dana Brooks and Dan White and Jess Tate and
+                 Rob S MacLeod",
+  journal =      "Available at SSRN 4049696",
+  year =         "2022",
 }
 
+@Article{JDT:Bur2020,
+  author =       "Kyle M. Burk and Akil Narayan and Joseph A. Orr",
+  title =        "Efficient sampling for polynomial chaos-based
+                 uncertainty quantification and sensitivity analysis
+                 using weighted approximate Fekete points",
+  journal =      "International Journal for Numerical Methods in
+                 Biomedical Engineering",
+  volume =       "36",
+  number =       "11",
+  pages =        "e3395",
+  keywords =     "approximate Fekete points, cardiovascular modeling,
+                 oxyhemoglobin dissociation, polynomial chaos expansion,
+                 sensitivity analysis, uncertainty quantification",
+  doi =          "https://doi.org/10.1002/cnm.3395",
+  year =         "2020",
+}
+
+@InProceedings{JDT:Ber2021,
+  author =       "Jake Bergquist and Brian Zenger and Lindsay Rupp and
+                 Akil Narayan and Jess Tate and Rob MacLeod",
+  title =        "Uncertainty Quantification in Simulations of
+                 Myocardial Ischemia",
+  booktitle =    "Computing in Cardiology",
+  month =        sep,
+  year =         "2021",
+  doi =          "",
+  volume =       "48",
+}
+
+@InProceedings{JDT:Rup2020,
+  author =       "Lindsay C Rupp and Zexin Liu and Jake A Bergquist and
+                 Sumientra Rampersad and Dan White and Jess D Tate and
+                 Dana H. Brooks and Akil Narayan and Rob S. MacLeod",
+  title =        "Using Uncertain{SCI} to Quantify Uncertainty in
+                 Cardiac Simulations",
+  booktitle =    "Computing in Cardiology",
+  month =        sep,
+  year =         "2020",
+  doi =          "",
+  volume =       "47",
+}
+
+@InProceedings{JDT:Rup2021,
+  author =       "Lindsay C Rupp and Jake A Bergquist and Brian Zenger
+                 and Karli Gillette and Akil Narayan and Jess Tate and
+                 Gernot Plank and Rob S. MacLeod",
+  title =        "The Role of Myocardial Fiber Direction in Epicardial
+                 Activation Patterns via Uncertainty Quantification",
+  booktitle =    "Computing in Cardiology",
+  month =        sep,
+  year =         "2021",
+  doi =          "",
+  volume =       "48",
+}
+
+@InCollection{JDT:Tat2021a,
+  author =       "Jess D. Tate and Wilson W. Good and Nejib Zemzemi and
+                 Machteld Boonstra and Peter van Dam and Dana H. Brooks
+                 and Akil Narayan and Rob S. MacLeod",
+  title =        "Uncertainty Quantification of the Effects of
+                 Segmentation Variability in {ECGI}",
+  booktitle =    "Functional Imaging and Modeling of the Heart",
+  publisher =    "Springer-Cham",
+  address =      "Palo Alto, USA",
+  editors =      "D. B. Ennis and L. E. Perotti and V. Y. Wang",
+  pages =        "515--522",
+  doi =          "https://doi.org/10.1007/978-3-030-78710-3_49",
+  year =         "2021",
+}
+
+@Article{JDT:Tat2021c,
+  author =       "Jess Tate and Sumientra Rampersad and Chantel
+                 Charlebois and Zexin Liu and Jake Bergquist and Dan
+                 White and Lindsay Rupp and Dana Brooks and Akil Narayan
+                 and Rob MacLeod",
+  booktitle =    "Brain Stimulation: Basic, Translational, and Clinical
+                 Research in Neuromodulation",
+  date =         "2021/11/01",
+  doi =          "10.1016/j.brs.2021.10.226",
+  ISBN =         "1935-861X",
+  journal =      "Brain Stimulation: Basic, Translational, and Clinical
+                 Research in Neuromodulation",
+  month =        jan,
+  number =       "6",
+  pages =        "1659--1660",
+  publisher =    "Elsevier",
+  title =        "Uncertainty Quantification in Brain Stimulation using
+                 Uncertain{SCI}",
+  ty =           "JOUR",
+  URL =          "https://doi.org/10.1016/j.brs.2021.10.226",
+  volume =       "14",
+  year =         "2021",
+}
+
+@InProceedings{JDT:Tat2022,
+  author =       "Jess D Tate and Nejib Zemzemi and Shireen Elhabian and
+                 Be\'{a}ta Ondru\u{s}ov\'{a} and Machteld Boonstra and
+                 Peter van Dam and Akil Narayan and Dana H Brooks and
+                 Rob S MacLeod",
+  booktitle =    "2022 Computing in Cardiology (CinC)",
+  title =        "Segmentation Uncertainty Quantification in Cardiac
+                 Propagation Models",
+  year =         "2022",
+  volume =       "498",
+  number =       "",
+  pages =        "1--4",
+  doi =          "10.22489/CinC.2022.419",
+}
+
+
 @article{narayan_computation_2018,
 	title = {Computation of induced orthogonal polynomial distributions},
 	volume = {50},