July 21, 2022
2022 Mizzou Faculty Alumni Awards – Notable Presence from MUIDSI
The 67th Annual Faculty Alumni Awardees were announced on July 20, 2022. Dr. Chi-Ren Shyu, MU IDSI Director; Dr. Lori Popejoy, MU IDSI Core Faculty and Interim Dean of Sinclair School of Nursing; and Dr. Dr. Stevan Whitt, Senior Associate Dean for Clinical Affairs of Medicine and MU IDSI’s long term physician collaborator, were among the six faculty awardees this year. According to Mizzou Alumni Association, “First celebrated in 1968, the Faculty Alumni Awards highlight the contributions of exceptional individuals to the University’s growth and core mission, through their professional accomplishments, teaching and research excellence or service to the institution.” To…
July 5, 2022
Dr. Popejoy leads MU Sinclair School of Nursing as Interim Dean
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May 19, 2022
GIScience as an Interdisciplinary Bridge in Indigenous Health Equity
GIS and geographic theories can help bridge a crucial gap in interdisciplinary research projects. Geography is uniquely poised to offer critical and practical analytical support, wrangle spatial data and relate them to other datasets, and ground community-based science within the communities it aims to serve. In the context of the Navajo Nation, a key concern is relating potential exposure to environmental contaminants with cultural identity and the social ramifications of resource extraction. Daniel Beene (DaRBeene@salud.unm.edu) is a Ph.D. student in the Department of Geography and Environmental Studies and a trainee with the METALS (Metals Exposure…
May 3, 2022
Dr. Blake Meyers Elected to the National Academy of Sciences
Dr. Blake Meyers, MUIDSI Informatics PhD program Core Faculty and Professor in the Division of Plant Science and Technology, and jointly appointed as a Principal Investigator and Member of the Donald Danforth Plant Science Center, has been elected as a Member of the US National Academy of Sciences. https://www.danforthcenter.org/news/blake-meyers-elected-to-national-academy-of-sciences/
May 3, 2022
Impact of diabetes status and other factors on risk for thrombotic and thromboembolic events: A multicenter, retrospective analysis using the Cerner Real-World DataTM de-identified COVID-19 cohort
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a proinflammatory condition that can impact the cardiovascular and cerebrovascular systems, thereby increasing risk for thrombotic and thromboembolic events (TTE). However, little is known about the impact of diabetes status on risk for TTEs during SARS-CoV-2 infection. In this US-based, multicenter retrospective cohort study, we analyze the impact of diabetes status (i.e., diabetes present vs. diabetes absent; Type 1 diabetes versus Type 2 diabetes), race and ethnicity, sex, and other factors on risk for TTEs in adults with suspected and confirmed COVID-19 infection. After using multivariate…
April 27, 2022
AMIA Informatics Summit Best Student Paper Award
By Karly Balslew On March 21st, doctoral student Humayera Islam won the American Medical Informatics Association (AMIA) Student Paper Competition award for the 2022 AMIA Informatics Summit that was held in Chicago. “It’s one of the biggest platforms for informatics people,” Islam said. “It’s very a very diverse and multidisciplinary platform where anybody that works in this area (informatics) can show their work.” Students from across the country submitted papers for AMIA 2022 Informatics Summit. Submitted papers then went through a peer-review process before judges selected the top five best papers. These top five were chosen to compete in the…
April 26, 2022
Analysis of polygenic selection in purebred and crossbred pig genomes using Generation Proxy Selection Mapping
Background Artificial selection on quantitative traits using selection indices in commercial livestock breeding populations causes changes in allele frequency over time, termed selection signatures, at causal loci and other surrounding genomic regions. Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection signature analyses. Here, we applied Generation Proxy Selection Mapping (GPSM), a genome-wide association analysis of SNP genotype (38,294 to 46,458 SNPs) on birth date, in four pig populations (15,457, 15,772, 16,595 and 8,447 pigs per population) to identify loci responding to artificial selection over a…
April 26, 2022
Comprehensive Exam: Using subgroup discovery techniques to identify a high-risk group of suicide attempts among people with diabetes
In 2019, 37.3 million Americans had diabetes mellitus, and 1.2 million Americans aged 18 and older had attempted suicide in the past year. According to previous studies, people with type 1 diabetes were three to four times more likely to attempt suicide, and newly diagnosed with type 2 diabetes were two times more likely to attempt suicide when compared with the general population. However, understanding the relationship between suicide attempts and other risk factors for people with diabetes is still lacking. In medical research, the data mining technique has become a promising way to effectively analyze high-dimensional data by extracting…
April 13, 2022
Detecting formation and growth of refugee / displaced person camps in the Ukraine crisis: Assisting first-phase humanitarian response using satellite imagery
Amid the worst population displacement crisis in Europe since World War 2, governments and international organizations have struggled with the massive task of tracking and providing aid to Ukrainian refugees and internally displaced persons (IDPs). This presentation reviews requirements and explores solutions for AI-assisted monitoring of formation of ad-hoc refugee encampments and temporary/informal settlements in remotely-sensed imagery to support time-critical humanitarian operations. Data and models for binary geospatial prediction of camp location as well as time-series camp expansion will be discussed, as will deep methods for characterizing similarities and differences among detected encampments.