Variant Processing Framework. by Myo T. Naung (10873278)

Implementation progress of PICC improvement strategies across 34 Michigan hospitals. by Gillian Ray-Barruel (3850969)

Frequency of vascular access committee meetings^a. by Gillian Ray-Barruel (3850969)

Data_Sheet_1_Cognitive Status Predicts Return to Functional Independence After Minor Stroke: A Decision Tree Analysis.docx by Mirjam R. Heldner (4476799)

“…The algorithm may help clinicians to tailor planning of patients' discharge.…”

Fig 12 - by Nisha Yadav (366131)

DataSheet_1_Abundance and Expression of Shiga Toxin Genes in Escherichia coli at the Recto-Anal Junction Relates to Host Immune Genes.pdf by Zhe Pan (426119)

Image_2_Rehabilitation Evidence-Based Decision-Making: The READ Model.TIF by Iona Novak (5576957)

Image_1_Rehabilitation Evidence-Based Decision-Making: The READ Model.TIF by Iona Novak (5576957)

Image_3_Rehabilitation Evidence-Based Decision-Making: The READ Model.TIF by Iona Novak (5576957)

Video_1_Deep Learning for Classification and Selection of Cine CMR Images to Achieve Fully Automated Quality-Controlled CMR Analysis From Scanner to Report.MP4 by Vittoria Vergani (4846690)

“…The framework consisted of a first pre-processing step to exclude still acquisitions; two sequential convolutional neural networks (CNN), the first (CNN_class) to classify acquisitions in standard cine views (2/3/4-chamber and short axis), the second (CNN_QC) to classify acquisitions according to image quality and orientation; a final algorithm to select one good acquisition of each class. …”

Figure 1 from Functional Genomic Identification of Predictors of Sensitivity and Mechanisms of Resistance to Multivalent Second-Generation TRAIL-R2 Agonists by Vera Grinkevitch (15089742)

Supplementary Material for: Effects of White Matter Hyperintensities on 90-Day Functional Outcome after Large Vessel and Non-Large Vessel Stroke by Griessenauer C.J. (8965901)

metropolis_hastings.py;postprocessing.py;folkman_a_b_c_time.py;figures_Inverse_Proliferation.R;README.md from Bayesian inference of a non-local proliferation model by Zuzanna Szymańska (11679819)

“…;Auxiliary R (version 3.6.2) code to generate figures presenting the results of the random walk Metropolis-Hastings algorithm for the Bayesian inference of a non-local proliferation function.…”

Full Counting Statistics of Phonon Thermal Transport for Disordered Systems by Chao Zhang (9218868)

Quick guide on how to calculate P/B and Q/B for Ecopath with Ecosim (EwE) models by Daniel Vilas (13621390)

Varying population size and source-finding approach: Simulated data. by Kelly Finke (10204631)

“…<p>The top panel shows the average reconstruction accuracy of chromosome 21 as a function of pre-migration population size. The bottom panel shows the number of reconstructed individuals for the corresponding scenarios. …”

Data_Sheet_1_Sensitivity of Inherent Optical Properties From Ocean Reflectance Inversion Models to Satellite Instrument Wavelength Suites.pdf by P. Jeremy Werdell (6526688)

Controlling Cumulative Adverse Risk in Learning Optimal Dynamic Treatment Regimens by Mochuan Liu (8177223)

“…In this work, we propose a general statistical learning framework to learn optimal DTRs that maximize the reward outcome while controlling the cumulative adverse risk to be below a pre-specified threshold. We convert this constrained optimization problem into an unconstrained optimization using a Lagrange function. …”

Multiscale Computational Framework for the Liquid–Liquid Phase Separation of Intrinsically Disordered Proteins by Kalindu S. Fernando (18271362)

“…The fluctuations of averaged radial distribution functions (RDFs) in successive MC trial move intervals of equilibrated lattice MC simulations were used to indicate the dynamic nature of assembly/disassembly of the protein chains. …”

Multiscale Computational Framework for the Liquid–Liquid Phase Separation of Intrinsically Disordered Proteins by Kalindu S. Fernando (18271362)

“…The fluctuations of averaged radial distribution functions (RDFs) in successive MC trial move intervals of equilibrated lattice MC simulations were used to indicate the dynamic nature of assembly/disassembly of the protein chains. …”