Reliability and reproducibility of perfusion MRI in cognitively normal subjects

Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is becoming a popular method for measuring perfusion due to its ability of generating perfusion maps noninvasively. This allows for frequent repeat scanning, which is especially useful for follow-up studies. However, limited information is available regarding the reliability and reproducibility of ASL perfusion measurements. Here, the reliability and reproducibility of pulsed ASL was investigated in an elderly population to determine the variation in perfusion among cognitively normal individuals in different brain structures. Intraclass correlation coefficients (ICC) and within-subject variation coefficients (wsCV) were used to estimate reliability and reproducibility over a period of 1 year. Twelve cognitively normal subjects (75.5±5.3 years old, six male and six female) were scanned four times (at 0, 3, 6 and 12 months). No significant difference in cerebral blood flow (CBF) was found over this period. CBF values ranged from 46 to 53 ml/100 g per minute in the medial frontal gyrus (MFG) and from 40 to 44 ml/100 g per minute over all gray matter regions in the superior part of the brain. Data obtained from the first two scans were processed by two readers and showed high reliability (ICC >0.97) and reproducibility (wsCV <6%). However, over the total period of 1 year, reliability reduced to a moderate level (ICC=0.63-0.74) with wsCVs of gray matter, left MFG, right MFG of 13.5%, 12.3%, and 15.4%, respectively. In conclusion, measurement of CBF with pulsed ASL provided good agreement between inter-raters. A moderate level of reliability was obtained over a 1-year period, which was attributed to variance in slice positioning and coregistration. As such pulsed ASL has the potential to be used for CBF comparison in longitudinal studies. © 2010 Elsevier Inc.postprin

Phase ordering on small-world networks with nearest-neighbor edges

We investigate global phase coherence in a system of coupled oscillators on a small-world networks constructed from a ring with nearest-neighbor edges. The effects of both thermal noise and quenched randomness on phase ordering are examined and compared with the global coherence in the corresponding \xy model without quenched randomness. It is found that in the appropriate regime phase ordering emerges at finite temperatures, even for a tiny fraction of shortcuts. Nature of the phase transition is also discussed.Comment: 5 pages, 4 figures, Phys. Rev. E (in press

Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network

The application of deep learning to symbolic domains remains an active research endeavour. Graph neural networks (GNN), consisting of trained neural modules which can be arranged in different topologies at run time, are sound alternatives to tackle relational problems which lend themselves to graph representations. In this paper, we show that GNNs are capable of multitask learning, which can be naturally enforced by training the model to refine a single set of multidimensional embeddings $\in \mathbb{R}^d$ and decode them into multiple outputs by connecting MLPs at the end of the pipeline. We demonstrate the multitask learning capability of the model in the relevant relational problem of estimating network centrality measures, focusing primarily on producing rankings based on these measures, i.e. is vertex $v_1$ more central than vertex $v_2$ given centrality $c$?. We then show that a GNN can be trained to develop a \emph{lingua franca} of vertex embeddings from which all relevant information about any of the trained centrality measures can be decoded. The proposed model achieves $89\%$ accuracy on a test dataset of random instances with up to 128 vertices and is shown to generalise to larger problem sizes. The model is also shown to obtain reasonable accuracy on a dataset of real world instances with up to 4k vertices, vastly surpassing the sizes of the largest instances with which the model was trained ($n=128$). Finally, we believe that our contributions attest to the potential of GNNs in symbolic domains in general and in relational learning in particular.Comment: Published at ICANN2019. 10 pages, 3 Figure

Evolution of community structure in the world trade web

In this note we study the bilateral merchandise trade flows between 186 countries over the 1948-2005 period using data from the International Monetary Fund. We use Pajek to identify network structure and behavior across thresholds and over time. In particular, we focus on the evolution of trade "islands" in the a world trade network in which countries are linked with directed edges weighted according to fraction of total dollars sent from one country to another. We find mixed evidence for globalization.Comment: To be submitted to APFA 6 Proceedings, 8 pages, 3 Figure

Integrating Data Science Ethics into an Undergraduate Major

We present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. We discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for weaving ethics into the curriculum from top-to-bottom as our majors progress from our introductory courses to our senior capstone course, as well as from side-to-side through co-curricular programming. We also provide six examples of data science ethics modules used in five different courses at our liberal arts college, each focusing on a different ethical consideration. The modules are designed to be portable such that they can be flexibly incorporated into existing courses at different levels of instruction with minimal disruption to syllabi. We conclude with next steps and preliminary assessments

Utilizing Three Years of Epidemiological Data from Medical Missions in Cambodia to Shape the Mobile Medical Clinic Formulary

Objective: The purpose of this project was to gather epidemiological data on common diseases and medications dispensed during medical mission teams to Cambodia to shape the mobile medical clinic formulary. Methods: Data for patients seen during week-long, mobile, medical clinics was collected in Cambodia during Septembers 2012 to 2014. Patient’s gender, age, weight, blood pressure, glucose, pertinent laboratory values, diagnoses, and medications dispensed were collected. Blood pressure and glucose were measured in patients 18 years and above. Data collected onto paper intake forms were transferred onto spreadsheets without patient identifying information and analyzed for aggregate means, common diseases, and most dispensed medications. This project received institutional review board approval. Results: A total of 1,015 patients were seen over three years. Women made up 61.4% and the mean age was 41.8 years. The most common diagnosis was gastrointestinal disorders (22.9%), which included gastroesophageal reflux disease and intestinal parasites. Next, 20.1% of patients had hypertension (BP\u3e140/90), 18.0% had presbyopia, 15.4% had back and joint pain, followed by 8.8% with headache, including migraines. Approximately 8.4% of patients had hyperglycemia (RPG \u3e140 mg/dl). Top five medications dispensed were acetaminophen, omeprazole, multivitamin, ibuprofen and metformin. For hypertension, amlodipine and lisinopril were dispensed. Conclusion: Cambodia lacks systematic public health collection of epidemiological data for prevalence of diseases. Hence, investigators collected and analyzed information from week-long mobile medical clinics over three years. Proton-pump inhibitors and H. pylori lab tests are recommended for gastrointestinal disorders. Acetaminophen and ibuprofen are recommended for pain. Angiotensin-converting-enzyme inhibitors and dihydropyridine calcium channel blockers are recommended over diuretics since patients are already dehydrated. Metformin is recommended for diabetes. Vitamins and supplements are recommended for malnourished patients. Hemoglobin machine and urine test strips are suggested. This information should help future teams decide what medications and laboratory tests are most beneficial on medical teams in Cambodia