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12 results on '"Yu, Jonathan W."'

4. Derivation and Validation of a Model to Predict Clinically Significant Portal Hypertension Using Transient Elastography and FIB-4

Author

Banini, Bubu A., primary, Patel, Samarth, additional, Yu, Jonathan W., additional, Kang, Le, additional, Bailey, Christopher, additional, Strife, Brian J., additional, Siddiqui, Mohammad S., additional, Patel, Vaishali, additional, Matherly, Scott C., additional, Lee, Hannah, additional, Lewis, Shawn, additional, Cherian, Reena, additional, Stravitz, Richard T., additional, Luketic, Velimir, additional, Sanyal, Arun J., additional, and Sterling, Richard K., additional

Published
2022
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8. Spike Train Correlation in Random Walk Integrate and Fire Neurons

Author

Yu, Jonathan W.

Subjects
Statistics, FOS: Mathematics
Abstract

One way to analyze how our brains function is to apply statistical models to neural data. In 1998, Shadlen and Newsome observed that a balanced random walk integrateand-fire model can model experimental data such as single-unit recordings of rhesus monkeys. Using this model, I study the spike count correlation of two neurons under varying conditions. Through simulations, I look at the relationship of spike count correlation across two neurons to firing input rate when the inputs are independent and correlated. After this step, I look at whether an oscillatory input affects synchrony, i.e., synchronous firing of two neurons in close temporal proximity. It is crucial to understand what affects synchrony as a little change in synchrony can cause huge impacts in cellular processes in the brain and in how neurons communicate with each other.

Published
2014
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9. Obesity does not significantly impact outcomes following simultaneous liver kidney transplantation: review of the UNOS database ‐ a retrospective study.

Author

Yu, Jonathan W., Kang, Le, Bandyopadhyay, Dipankar, Gupta, Gaurav, Siddiqui, Mohammed S., Stravitz, Richard T., Bhati, Chandra S., Levy, Marlon, and Reichman, Trevor W.

Abstract

Summary: Simultaneous liver kidney transplantation (SLK) is the only curative option for patients with combined end stage liver and kidney disease. With the global obesity epidemic, an increasing number of obese patients are in need of SLK. However, the impact of pre‐transplant obesity on outcomes after SLK is unknown. An analysis of the United States OPTN registry (Oct 1987 – June 2016) identified 7205 SLK transplants. Of these, 1677 patients were overweight/obese (OW, BMI 30–39) and 183 were morbidly obese (MO, BMI ≥40). 29% of patients had NASH in the MO group versus 16.4% and 4.7% in the OW and normal weight (NW) groups, respectively. The 1, 3 and 5 year overall patient survival, kidney and liver graft survivals were comparable between the three groups. Numerically higher rates of acute kidney rejection were reported in the MO group at 1 year [12.73%, 8.59%, and 10.05% for MO, OW and NW, respectively (P = 0.22)]. Multivariate analysis identified diagnosis of hepatitis C, donor age, diabetes mellitus, and delayed kidney transplant function but not BMI as risk factors for poor patient and both liver and kidney graft survival. Based on these findings, obesity should not be a contraindication for SLK even for patients with BMIs ≥ 40. [ABSTRACT FROM AUTHOR]

Published
2019
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11. Using Incremental Worked Examples for Teaching Python and Game Programming.

Author

Yang, Cheer-Sun D. and Yu, Jonathan W.

Subjects
*PYTHON programming language, *ACTIVE learning, *MACHINE learning, *COMPUTER science education, *COMPUTER game programming, *COMPUTER programming
Abstract

While world economy remains stagnant, enrollment in Computer Science suffers inevitably. A computer science educator must find innovative ways to inspire students for learning computing technologies. Active learning with "worked examples", presented by Sweller and Cooper, has been proven to be an effective pedagogical strategy. However, when teaching Python with Game Building using the active learning approach, an instructor may run into several challenges. First, developing games requires certain familiarity with the programming language and mathematic. Without the prerequisites, students may not be able to participate in discussions actively. Second, learning game building can become extraneous cognitive load instead of incentives for learning python programming especially for students without knowing python. In this paper, an incremental model is presented for teaching python programming with game building. These incremental lab projects are easy to learn, easy to implement, and relevant with the targeted subjects. As a result of using the incremental projects, students become motivated; many, if not all, actively participate in the discussion about various subjects. The experiences learned are discussed. Student projects are briefly described. Finally, future work is included. [ABSTRACT FROM AUTHOR]

Published
2011
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