Suresh K Bhavnani

University of Texas Medical Branch at Galveston | UTMB · Department of Preventive Medicine & Population Health

Abstract Introduction Considerable progress has been made in researching the development and effectiveness of translational scientific research teams, particularly within the Science of Team Science (SciTS). A recent literature review revealed no studies that explored teams which used an explicit theoretical framework for multiteam systems in acade...

OBJECTIVES/GOALS: A growing number of older adults in the United States have multiple social determinants of health (SDoH) that are barriers to effective medical care. We used generalizable machine learning methods to identify and visualize subtypes based on participant-reported SDoH profiles, and their association with delayed medical care (self-r...

OBJECTIVES/GOALS: While disease subtypes are critical for precision medicine, most projects use unipartite clustering methods such as k-means which are not fully automated, do not provide statistical significance, and are difficult to interpret. These gaps were addressed through bipartite networks and tested for generalizability on three national d...

OBJECTIVES/GOALS: This report evaluates participants’experiences from three universities who assembled a complex grant proposal related to research on post-acute sequala of COVID-19 (PASC), also called long COVID. Activities reviewed ranged from the assembly of the team to responses to reviews by the National Center for Advancing Translational Scie...

Objectives: Managing multimorbidity as aging stroke patients is complex; standard self-management programs necessitate adaptations. We used visual analytics to examine complex relationships among aging stroke survivors’ comorbidities. These findings informed pre-adaptation of a component of the Chronic Disease Self-Management Program. Methods: Seco...

OBJECTIVES/GOALS: Approximately 10% of COVID-19 patients experience multiple symptoms weeks and months after the acute phase of infection. Our goal was to use advanced machine learning methods to identify PASC phenotypes based on their symptom profiles, and their association with critical adverse outcomes, with the goal of designing future targeted...

Background A primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes, with the aim of designing targeted interventions. However, few methods automatically identify both patient subgroups and their co-occurring characteristics simultaneously, measure their significance, and visualize the resul...

BACKGROUND A primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes, with the aim of designing targeted interventions. However, few methods automatically identify both patient subgroups and their co-occurring characteristics simultaneously, measure their significance, and visualize the resul...

Background: A primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes, with the aim of designing targeted interventions. However, while several studies have identified patient subgroups, there is a considerable gap between the identification of patient subgroups, and their modeling and inter...

Biomarkers for prognosis-based detection of Trypanosoma cruzi-infected patients presenting no clinical symptoms to cardiac Chagas disease (CD) are not available. In this study, we examined the performance of seven biomarkers in prognosis and risk of symptomatic CD development. T. cruzi-infected patients clinically asymptomatic (C/A; n = 30) or clin...

Several studies have shown that COVID-19 patients with prior comorbidities have a higher risk for adverse outcomes, resulting in a disproportionate impact on older adults and minorities that fit that profile. However, although there is considerable heterogeneity in the comorbidity profiles of these populations, not much is known about how prior com...

Date Presented 03/26/20 Using big data visual analytics and a total of 86,887 readmitted Medicare beneficiaries living with stroke, a number of biclusters consisting of patient subgroups and their co-occurring multiple chronic comorbidities were determined. This technique informed a multimorbidity self-management program to support patients managin...

PURPOSE Our goal was to identify the opportunities and challenges in analyzing data from the American Association of Cancer Research Project Genomics Evidence Neoplasia Information Exchange (GENIE), a multi-institutional database derived from clinically driven genomic testing, at both the inter- and the intra-institutional level. Inter-institutiona...

2050 Background: Hormone receptor-positive (HR+), HER2-negative (HER2-) metastatic breast cancer (MBC) is treated with targeted therapy, hormone therapy, chemotherapy, or combinations of these modalities. Evaluating the increasing number of treatment options is challenging, especially since few regimens have been compared head-to-head in randomized...

Background: mRNA interaction with other mRNAs and other signaling molecules determine different biological pathways and functions. Gene co-expression network analysis methods have been widely used to identify correlation patterns between genes in various biological contexts (e.g., cancer, mouse genetics, yeast genetics). A challenge remains to ide...

To enable high-powered multi-site studies, numerous healthcare organizations are attempting to harmonize their electronic health records (EHRs) with common data models such as PCORnet and ACT. However, the harmonization process is known to be difficult, requiring extensive manual curation by domain experts. Here we report on a case study of harmoni...

Background When older adult patients with hip fracture (HFx) have unplanned hospital readmissions within 30 days of discharge, it doubles their 1-year mortality, resulting in substantial personal and financial burdens. Although such unplanned readmissions are predominantly caused by reasons not related to HFx surgery, few studies have focused on ho...

BACKGROUND When older adult patients with hip fracture (HFx) have unplanned hospital readmissions within 30 days of discharge, it doubles their 1-year mortality, resulting in substantial personal and financial burdens. Although such unplanned readmissions are predominantly caused by reasons not related to HFx surgery, few studies have focused on ho...

A critical goal of multidisciplinary scientific teams is to integrate knowledge from diverse disciplines for the purpose of developing novel insights and innovations. For example, multidisciplinary translational teams (MTTs) which typically include physicians, biologists, statisticians, and informaticians, aim to integrate biological and clinical k...

A primary goal of precision medicine is to identify patient subgroups based on their characteristics (e.g., comorbidities or genes) with the goal of designing more targeted interventions. While network visualization methods such as Fruchterman-Reingold have been used to successfully identify such patient subgroups in small to medium sized data sets...

Background: Recent studies have shown that epigenetic differences can increase the risk of spontaneous preterm birth (PTB). However, little is known about heterogeneity underlying such epigenetic differences, which could lead to hypotheses for biological pathways in specific patient subgroups, and corresponding targeted interventions critical for...

Although a majority of 30-day readmissions of hip-fracture (HFx) patients in the elderly are caused by non-surgical complications, little is known about which specific combinations of comorbidities are associated with increased risk of readmission. We therefore used bipartite network analysis to explore the complex associations between 70 comorbidi...

Background The airway epithelial cell plays a central role in coordinating the pulmonary response to injury and inflammation. Here, transforming growth factor-β (TGFβ) activates gene expression programs to induce stem cell-like properties, inhibit expression of differentiated epithelial adhesion proteins and express mesenchymal contractile protein...

There is growing consensus about the factors critical for development and productivity of multidisciplinary teams, but few studies have evaluated their longitudinal changes. We present a longitudinal study of 10 multidisciplinary translational teams (MTTs), based on team process and outcome measures, evaluated before and after 3 years of CTSA colla...

Despite years of preclinical development, biological interventions designed to treat complex diseases like asthma often fail in phase III clinical trials. These failures suggest that current methods to analyze biomedical data might be missing critical aspects of biological complexity such as the assumption that cases and controls come from homogene...

The exponential growth of biomedical information far exceeds our cognitive abilities to comprehend it for the prevention, diagnosis, and treatment of complex diseases. This chapter discusses the cognitive and task-based reasons for why methods from visual analytics can help in analyzing such large and complex data, and demonstrates how one such app...

Although influenza (flu) and respiratory syncytial virus (RSV) infections are extremely common in children under two years and resolve naturally, a subset develop severe disease resulting in hospitalization despite having no identifiable clinical risk factors. However, little is known about inherent host-specific genetic and immune mechanisms in th...

The exponential growth of biomedical data related to diseases such as asthma far exceeds our cognitive abilities to comprehend it for tasks such as biomarker discovery, pathway identification, and molecular-based phenotyping. This chapter discusses the cognitive and task-based reasons for why methods from visual analytics can help in analyzing such...

A critical goal of outlier detection is to determine whether an outlying value was caused by experimental/human error, or by natural biological diversity. However, because univariate or multivariate methods (e.g., box plots and principle component analysis) typically used for outlier detection use unipartite representations, they cannot distinguish...

Several intersecting host, vector, and environmental factors have led to a re-emergence of rickettsial diseases such as Mediterranean Spotted Fever (MSF), and Dermacentor spp.-borne necrosis-erythema lymphadenopathy (DEBONEL). Some rickettsiae produce diffuse endothelial infection and systemic microvascular leakage leading in some cases to high mor...

Translational science requires that scientists from multiple disciplines work together to improve the prevention, diagnosis, and treatment of human disease. Although a literature exists on the design and management of multidisciplinary teams, little has been written on multidisciplinary translational teams (MTTs). MTTs are distinct hybrid entities,...

The problem of active diagnosis arises in several applications such as disease diagnosis and fault diagnosis in computer networks, where the goal is to rapidly identify the binary states of a set of objects (e.g., faulty or working) by sequentially selecting, and observing, potentially noisy responses to binary valued queries. Previous work in this...

Asthma is a chronic inflammatory disease of the airways that leads to various degrees of recurrent respiratory symptoms affecting patients globally. Specific subgroups of asthma patients have severe disease leading to increased healthcare costs and socioeconomic burden. Despite the overwhelming prevalence of the asthma, there are limitations in pre...

A critical aspect of clinical and translational science (CTS) is interdisciplinary and collaborative research, which increasingly requires a wide range of computational and human resources. However, few studies have systematically analyzed such resource needs of CTS researchers. To improve our understanding of CTS researchers' needs for computation...

Prediction of mortality in severely burned patients remains unreliable. Although clinical covariates and plasma protein abundance have been used with varying degrees of success, the triad of burn size, inhalation injury, and age remains the most reliable predictor. We investigated the effect of combining proteomics variables with these three clinic...

Objective Several studies have shown how sets of single-nucleotide polymorphisms (SNPs) can help to classify subjects on the basis of their continental origins, with applications to case–control studies and population genetics. However, most of these studies use dimensionality-reduction methods, such as principal component analysis, or clustering m...

The problem of active diagnosis arises in several applications such as disease diagnosis, and fault diagnosis in computer networks, where the goal is to rapidly identify the binary states of a set of objects (e.g., faulty or working) by sequentially selecting, and observing, (noisy) responses to binary valued queries. Current algorithms in this are...

Translational bioinformatics increasingly involves the discovery of associations between molecular and phenotype information, with the goal of transforming those discoveries into novel methods for diagnosis and treatment. To enable such complex analysis, researchers need approaches that provide the simultaneous representation and interactive analys...

In applications such as active learning and disease/fault diagnosis, one often encounters the problem of identifying an unknown object through a minimal number of queries. This problem has been referred to as query learning or object/entity identification. We consider three extensions of this fundamental problem that are motivated by practical cons...

Asthmatic patients are currently classified as either severe or non-severe based primarily on their response to glucocorticoids. However, because this classification is based on a post-hoc assessment of treatment response, it does not inform the rational staging of disease or therapy. Recent studies in other diseases suggest that a classification w...

We consider a problem of active diagnosis, where the goal is to efficiently identify an unknown object by sequentially selecting, and observing, the responses to binary valued queries. We assume that query observations are noisy, and further that the noise is persistent, meaning that repeating a query does not change the response. Previous work in...

The growing influx of information and communication technologies (ICTs) into rural India provides new opportunities for the prevention and treatment of diseases across millions of residents. However, little is known about how rural Indians with little or no exposure to computers perceive computers and their uses, and how best to elicit those percep...

In this paper, we report a qualitative study of translational researchers in health sciences in a large public Research I university in the United States. This paper first identifies challenges faced by translational researchers in mobilizing necessary resources such as data and personnel to effectively conduct research. Then we use the theoretical...

A comprehensive understanding of evidence related to treatments for a disease is critical for planning effective clinical care, and for designing future trials. However, it is often difficult to comprehend the available evidence because of the complex combination of interventions across trials, in addition to the limited search and retrieval tools...

In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pa...

Although many cancer patients experience multiple concurrent symptoms, most studies have either focused on the analysis of single symptoms, or have used methods such as factor analysis that make a priori assumptions about how the data is structured. This article addresses both limitations by first visually exploring the data to identify patterns in...

Despite the development of huge healthcare Web sites and powerful search engines, many searchers end their searches prematurely with incomplete information. Recent studies suggest that users often retrieve incomplete information because of the complex scatter of relevant facts about a topic across Web pages. However, little is understood about regu...

In query learning, the goal is to identify an unknown object while minimizing the number of "yes" or "no" questions (queries) posed about that object. A well-studied algorithm for query learning is known as generalized binary search (GBS). We show that GBS is a greedy algorithm to optimize the expected number of queries needed to identify the unkno...

In query learning, the goal is to identify an unknown object while minimizing the number of "yes or no" questions (queries) posed about that object. We consider three extensions of this fundamental problem that are motivated by practical considerations in real-world, time-critical identification tasks such as emergency response. First, we consider...

Chronic renal diseases are currently classified based on morphological similarities such as whether they produce predominantly inflammatory or non-inflammatory responses. However, such classifications do not reliably predict the course of the disease and its response to therapy. In contrast, recent studies in diseases such as breast cancer suggest...

No Abstract. Peer Reviewed http://deepblue.lib.umich.edu/bitstream/2027.42/61334/1/1450440124_ftp.pdf

Current interfaces and help facilities of CAD systems are not designed to respond to a user's performance. To develop such adaptive environments, a better understanding of the indicators of CAD experience is required. This paper discusses the results of studying behavior patterns of different types and levels of CAD users for a specific drawing tas...

Numerous studies have shown that many users do not acquire the knowledge necessary for the effective and efficient use of computer applications such as spreadsheets and Web-authoring tools. While many cognitive, cultural, and social reasons have been offered to explain this phenomenon, there have been few systematic attempts to address it. This art...

Despite the large number of patent searches conducted by professional patent searchers and inventors, little is known about how such searches are actually performed. Here we describe a qualitative study of experienced patent searchers as they conducted in-context searches at a technology transfer office. Based on studies of expert search and sensem...

First-responders have a critical need to rapidly identify toxic chemicals during emergencies. However, current systems such as WISER require a large number of inputs before a chemical can be identified. Here we present a novel system which significantly reduces the number of inputs required to identify a toxic chemical.

Numerous studies have shown that many users do not acquire the knowledge necessary for the effective and efficient use of computer applications such as spreadsheets and Web-authoring tools. While many cognitive, cultural, and social reasons have been offered to explain this phenomenon, there have been few systematic attempts to address it. This art...

Recent studies suggest that users often retrieve incomplete healthcare information because of the complex and skewed distribution of facts across relevant webpages. To understand the causes for such skewed distributions, this paper presents the results of two analyses: (1) A distribution analysis discusses how facts related to healthcare topics are...

Information on any given topic is often scattered across the Web. Previously this scatter has been characterized through the inequality of distribution of facts (i.e. pieces of information) across webpages. Such an approach conceals how specific facts (e.g. rare facts) occur in specific types of pages (e.g. fact-rich pages). To reveal such regulari...

The rapid and accurate identification of toxic chemicals is critical for saving lives in emergency situations. However, first-responder systems such as WISER typically require a large number of inputs before a chemical can be identified. To address this problem, we used networks to visualize and analyze the complex relationship between toxic chemic...