Comprehensive Exam Announcement – A Case-Control based Genomic Analysis of Chronic Obstructive Pulmonary Disease
Chronic Obstructive Pulmonary Disease (COPD) is a respiratory illness that affects millions of people all over the world. It is a major cause of chronic morbidity and mortality and a serious global public health problem. COPD is the fourth leading cause of death worldwide. Although the environmental causes of COPD which predominantly include cigarette smoking are well-documented, to this date the genetic underpinnings of COPD remain largely unknown. Furthermore, in the current landscape of a respiratory pandemic, COPD patients are at a much higher risk for developing other respiratory illnesses and co-morbidities. In this study we use genomic data from…
Regulation of gene expression by DNA methylation with cytotoxic T lymphocytes evaluation in consensus molecular subtypes of colorectal cancer
Background: Low cytotoxic T lymphocyte (CTLs) infiltration in colorectal cancer (CRC) tumors is a challenge to treatment with immune checkpoint inhibitors. Consensus molecular subtypes (CMS) classify patients based on tumor attributes, and CMS1 patients include the majority of patients with high CTL infiltration and “inflamed” tumors. Epigenetic modification plays a critical role in gene expression and therapy resistance. Therefore, in this study we compared DNA methylation, gene expression, and CTL infiltration of CMS1 patients to other CMS groups to determine targets for improving immunotherapy in CRC. Furthermore, we used transcriptome of 91,103 unsorted scRNAseq to validate bulk RNA finding. Results…
Leveraging Unsupervised Machine Learning To Find Trends In The Textual Warnings Generated Using Multi-Modality Time Series Sensor Data
With technology and the internet of things (IoT), smart health care is no longer a dream. The devices that wouldn’t usually be generally expected to have an internet connection can communicate with the network independent of human action, and this is referred to as the internet of things. These devices, in our case, are the sensors placed in the elderly assisted living facility Tiger Place. Sensors include the ballistocardiogram (bed sensor) and motion sensors placed in the living room, bathroom, kitchen, etc. These sensors help in measuring nine major features, which defines the per-day activities of each elderly resident in the…
Information Extraction Framework for Facilitating the Assessment of the Quality of Radiology Interpretations
Assessing the quality of imaging interpretations requires that the results of radiological interpretations be compared with those of subsequent surgical-pathology results, when available. The manual process is inherently slow, tedious and expensive, and unless systematic errors occur in the interpretations, discrepancies are unlikely to be detected. Classical computational methods using Natural Language Processing entail using a corpus of annotated documents for model development and evaluation. However, developing such a corpus is also very expensive and time consuming, and the output is usually not portable between medical institutions. To alleviate these issues we are proposing a statistical learning method for textual…
Abnormal liver function and adverse health outcomes in COVID-19: A multicenter, retrospective analysis of 14,872 patients from 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), has been associated with liver impairment and abnormalities in liver function tests. However, associations between hepatic impairment and patient health outcomes have not been well-studied in large cohorts. In this US-based, multicenter retrospective cohort study, we analyze the impact of abnormalities in liver function tests at admission on mortality and adverse health outcomes in patients with laboratory-confirmed COVID-19 infection. Propensity score analysis and a full matching algorithm were used to minimize dissimilarity in covariates thought to impact outcomes of interest and to isolate the effect of liver abnormalities on patient…
Thyroid Cancer Informatics
Survival prediction is important both to clinicians and patients; ensuring the best course of treatment is selected to manage the thyroid cancer. In 2018, there was an estimated half a million new thyroid cancer diagnoses and 41,071 deaths. Unlike other tumors whose mortality has decreased over the last two decades, thyroid cancer mortality rates have increased. Existing risk stratification systems fail to account for microcarcinomas, which accounted for 28.6 percent of thyroid cancer diagnoses and 32.5 percent of papillary thyroid cancer diagnoses. They are also based upon a varying combination of 10 variables and have not considered newly identified variables available in current research. Additionally,…
A Case-Control based Genomic Analysis of Chronic Obstructive Pulmonary Disease
Chronic Obstructive Pulmonary Disease (COPD) is a respiratory illness that affects millions of people all over the world. It is a major cause of chronic morbidity and mortality and a serious global public health problem. COPD is the fourth leading cause of death worldwide. Although the environmental causes of COPD which predominantly include cigarette smoking are well-documented, to this date the genetic underpinnings of COPD remain largely unknown. Furthermore, in the current landscape of a respiratory pandemic, COPD patients are at a much higher risk for developing other respiratory illnesses and co-morbidities. In this study we use genomic data from…
Methods for Measuring Geodiversity in Large Overhead Imagery Datasets
This research introduces some of the first geo-computational methods to address a key gap in the artificial intelligence (AI) and big data literature as it relates to the geosciences and remote sensing: the lack of understanding of the global feature representativeness of labels in large remotely-sensed imagery (RSI) datasets. Issues of data fairness, heterogeneity and equitability – often related directly to geographic and demographic under-sampling – have recently come to the fore in multidisciplinary discussions of the ethics of AI. The risks of perpetuating data and models with unknown biases are particularly heightened in the air-and space-born RSI domain, given…
The Genescape Allele Catalog Development for Precise Identification of Causative SNPs
Next-generation sequencing (NGS) has become more popular in the modern-day. Large amounts of next-generation resequencing data have been generated and are available online for various organisms including soybeans. However, current genome-wide association study (GWAS) prediction tools simply identify the most significant SNP based on Manhattan plots and still have some limitations in pinpointing the exact causative SNPs using the SNP array or NGS datasets. Therefore, we are developing a Genescape catalog, a new bioinformatics approach to integrate all potential alleles for all genes in soybean genome using the genomic variations and phenotypic information from a large subset of cultivated and…