A Data Analytics Framework for Improving the Efficiency of Stroke Imaging Investigations

Emergency departments are under tremendous pressure to provide high-quality care in the shortest amount of time possible. While not all cases seen in the ED are urgent in nature, some require immediate attention. These true emergencies are usually complex in nature and depend on people, processes and technologies to work seamlessly, in perfect orchestration, in order to achieve the desired outcomes for the patient. One such condition is the stroke, a condition which left untreated (or treated incorrectly) can lead to devastating debilities and even death. To treat stroke successfully, a correct imaging diagnostic needs to be placed and treatment…

Real-time prediction of unplanned 30-day hospital readmissions

Hospital readmissions are frequent and costly. It has been estimated that unplanned readmissions account for $17.4 billion in Medicare expenditures annually. Since the fiscal year 2013, the Hospital Readmissions Reduction Program (HRRP) has been established to financially penalize hospitals with excessive readmissions after initial admissions for particular conditions and procedures. In recent years, numerous hospital readmission predictive models have been reported and most of them rely on attributes that are only available near or post-discharge of the current encounter, such as the length of stay, discharge disposition, diagnosis codes. By incorporating these attributes, it is impossible to perform real-time readmission prediction during…

Medical Calculators: Prevalence, and Barriers to Use

Medical calculators synthesize measurable evidence and help introduce new medical guidelines and standards.   Some medical calculators can fulfill the role of CDS for Meaningful Use purposes.  However, there are barriers for clinicians to use medical calculators in practice.  Objectives of this study were to determine whether lack of EHR integration would be a barrier to use of medical calculators and understand factors that may limit use and perceived usefulness of calculators A survey about medical calculators as they relate to clinical efficiency, perceived usefulness, and barriers to effective use was conducted at a medium-sized academic medical center.  819 physicians were…

Application of Deep Learning in Predicting Phenotypes

Genomic selection (GS) can use single-nucleotide polymorphism (SNPs) markers to predict breeding values (BV) for enhancing quantitative traits in breeding populations. GS has been proved to increase breeding efficiency in both plant and animal breeding. However, existing statistical and machine-learning methods require imputation to missing values in genotypes, which leads to poor generalization and computation inefficiency. Here, we propose a deep-learning model using convolutional neural networks (CNN) to predict the Genomic Estimated Breeding Value (GEBV) and also to investigate contributions of genomic SNPs to GEBV using a saliency map approach.Comparing with traditional statistical models including rr-BLUP, Bayesian ridge regression, Bayesian…

Volumetric Analysis of Adipose Tissue

Body Condition Score is the veterinary equivalent of BMI in humans, in which veterinarians attempt to assess adiposity of an animal and make appropriate recommendations. However, this measure of adiposity is fairly subjective and quite variable depending on the species being analyzed. Thus, a more quantifiable and objective measure of adiposity, through the utilization of initially CT scans and subsequently through radiographs would be beneficial. CT scans were taken from the University of Missouri Veterinary Health Center PACS from patients who had received thoracic CT scans, a full body CT scan, as well as a thoracic and abdominal CT scan.

Investigating Genome Compositional Features of Apis and other Hymenopteran Species

Initial analysis of the honey bee (Apis mellifera) genome in 2006 revealed several interesting features compared to other metazoan genome sequences available at that time: a low but heterogeneous GC content, an overabundance of CpG dinucleotides and a lack of repetitive elements. The average GC content of the honey bee genome is only 33%, but GC content is highly heterogeneous, ranging from 11% to 67%, with a bimodal distribution. Furthermore, unlike genes in most other metazoans, honey bee genes are overly abundant in regions of low GC content (<30%). It is unclear whether any of these genome features are related…

Translational 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 will be 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 not decreased, the have increased.  Existing risk stratification systems fail to account for microcarcinomas, which accounted for 28.6 percent of thyroid cancers and 32.5 percent of papillary thyroid cancer.  They are also based upon a varying combination of 10 variables and have not considered…

Using Deep Convolutional Neural Networks To Detect And Classify Indicators Of Leukemia In Blood Samples

The successful detection of leukemia depends on the correct interpretation of the lineage and morphology of monocytes — a type of white blood cells. The monocytes have been classified into four primary stages of differentiation. However, the stages cannot be distinguished unambiguously even by panels of trained experts. A number of attempts have been made to create tissue classifiers using deep learning that did not specifically address monocyte morphology. This research attempts to leverage whole-slide imaging and deep learning tools to create an automated high-accuracy method for cancerous monocytic cell detection.

Study of A Visualization Tool Development in Health Informatics

The volume and complexity of data continue to increase in the world around us, including science, business, medicine and everyday human activity. Handling these diverse data to simple and intuitive representation, using simple design and intuitive interaction for non-informatics or non-statistics expert is a pursuance for informatics researchers. Nowadays, the data visualization technology and the internet can bring meaningful information to meet the specific user needs due to it not only presents a visual data interpretation but also improves comprehension and communication with users.  As an example, autism (ASD, Autism Spectrum Disorder) is a disease considered to be a neurodevelopment disorder…