IDSI PhD student Will Baskett crunched EHR data, finding only a few long-haul symptoms directly related to COVID in comparison to generic viral infection
In a new study, a team of University of Missouri researchers made an unexpected discovery: people experiencing long-lasting effects from COVID-19 — known as “long COVID” or post-COVID conditions — are susceptible to developing only seven health symptoms for up…
Two IDSI Core Faculty Elected as Fellow of AAAS
Dr. Xiu-Feng “Henry” Wan and Dr. Xiaoqin Zou were named as Fellows of the American Association for the Advancement of Science. Read More…
Identification of Spatially Variable Genes
Invasive species pose a unique threat to native species and habitat through direct and indirect competition of resources. Management of invasive species depends on precise identification of their current range and knowledge of how they spread. This project will utilize…
Modeling Pyrus calleryana spread in central Missouri using remote sensing and a non-parametric modeling approach
Invasive species pose a unique threat to native species and habitat through direct and indirect competition of resources. Management of invasive species depends on precise identification of their current range and knowledge of how they spread. This project will utilize…
Relationships between mortality and respiratory health, medication usage, water disappearance, and climatic conditions in commercial weaning-to-finishing pigs
Mortality in pigs is of paramount economic importance to United States pig producers. According to data compiled by MetaFarms SMS and Pork Checkoff in 2022, 21.2% of pigs die before reaching slaughter, and this statistic has increased, in general, over the…
DeepVariant – TrioTrain: Developing a transfer learning protocol using non-human genomes
Genomic data are widely available for investigating phenotypes that impact both human and animal health. Although the investigation of human health often begins with model organisms, genomics technologies and software are often initially developed with only the human genome in…
MUIDSI DISSERTATION DEFENSE – ACCELERATING DATA-DRIVEN DISCOVERY IN TYPE 1 DIABETES: AN INFORMATICS-BASED APPROACH
Type 1 diabetes (T1D) is a lifelong chronic disease characterized by the absolute or near-absolute loss of insulin. For affected individuals, management of T1D is an unremitting challenge that involves constant blood glucose monitoring and lifelong administration and titration of…
A combined AI approach to biomedical data analysis: Knowledge representation reasoning, machine learning and explainable AI
In this talk, I will explore if and how two traditionally distinct fields of AI, that is, ontology engineering and machine learning can be combined to improve performance outcomes. Using real world examples from epilepsy neurological disorder, the talk will demonstrate the use of…
MUIDSI Dissertation Defense: IDENTIFICATION OF IMMUNE-RELATED GENE SIGNATURES TO EVALUATE IMMUNOTHARAPEUTIC RESPONSE IN CANCER PATIENTS USING EXPLORATORY SUBGROUP DISCOVERY
Phenotypic and genotypic heterogeneity are characteristic features of cancer patients. To tackle patients’ heterogeneity, immune checkpoint inhibitors (ICIs) represent one of the most promising therapeutic approaches. However, approximately 50% of cancer patients that are eligible for treatment with ICIs will…