A5052549427- Biomedical Text Mining and Ontologies
- Metabolomics and Mass Spectrometry Studies
- Bioinformatics and Genomic Networks
- Genetics, Bioinformatics, and Biomedical Research
- Diet and metabolism studies
- Electronic Health Records Systems
- Machine Learning in Healthcare
- Genomics and Rare Diseases
- Ethics in Clinical Research
- Radiomics and Machine Learning in Medical Imaging
- Alzheimer's disease research and treatments
- Health Systems, Economic Evaluations, Quality of Life
- Data Quality and Management
- Scientific Computing and Data Management
- Computational Drug Discovery Methods
- Lung Cancer Diagnosis and Treatment
- Digital Mental Health Interventions
- Advances in Oncology and Radiotherapy
- Genetic Associations and Epidemiology
- Advanced Biosensing Techniques and Applications
- Monoclonal and Polyclonal Antibodies Research
- Metabolism and Genetic Disorders
- Drug Transport and Resistance Mechanisms
- Public Health Policies and Education
- Gut microbiota and health
Duke University
2014-2024
NC Department of Health and Human Services
2020-2022
North Carolina Division of Public Health
2022
Duke Medical Center
2021
Clinical Research Institute
2019
Baum Consult
2016
Durham University
2012
Stanford Medicine
2006
Abstract Introduction Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and specific gut‐brain axis neurodegeneration. Bile acids (BAs), products of cholesterol metabolism clearance, are produced liver further metabolized by bacteria. They have major regulatory signaling functions seem dysregulated Alzheimer's disease (AD). Methods Serum levels 15 primary secondary BAs their conjugated forms were measured 1464 subjects including 370 cognitively...
Abstract Introduction The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, nonprofit organizations to develop new research directions transform our understanding disease (AD) propel the development critically needed therapies. In response their recommendations, big data at multiple levels are being generated integrated study network failures in disease. We used metabolomics as a global biochemical approach identify peripheral metabolic...
Late-onset Alzheimer's disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large differences. We systematically investigated group-specific alterations by conducting stratified association analyses of 139 serum metabolites 1,517 individuals from the Neuroimaging Initiative with biomarkers. observed substantial differences effects 15 partially overlapping status groups. Several...
Abstract Background This article addresses the problem of interoperation heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing database warehouses using MySQL and Oracle relational managers. BioWarehouse integrates its component databases into a common representational framework within single management system, thus enabling multi-database queries Structured Query Language (SQL) but also facilitating variety integration tasks such...
Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result unnecessary delays understanding, predicting, preparing for, containing, and mitigating COVID-19 pandemic US. Response involve collection analysis data corresponding healthcare organizations, public health departments, socioeconomic indicators, as well additional signals collected directly from individuals communities. We focused on electronic record (EHR) data, since EHRs...
Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation hospitalization). Machine learning (ML) may guide interventions to reduce this risk. There are limited prospective studies investigating the clinical impact of ML in health care. The objective study was determine whether can identify high-risk patients and direct mandatory twice-weekly visits during treatment.During single-institution randomized quality...
Abstract Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action not fully understood and therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing panel 180 metabolites to gain insights into response citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study...
Abstract The recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue evolve datasets grow in magnitude, a strong computational infrastructure will be essential realize PM’s vision improved derived from personal data. In addition, informatics research innovation affords tremendous opportunity drive science underlying...
Abstract Alzheimer’s disease (AD) is the most common neurodegenerative presenting major health and economic challenges that continue to grow. Mechanisms of are poorly understood but significant data point metabolic defects might contribute pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Neuroimaging Initiative (ADNI) creating a comprehensive biochemical database for AD. Using targeted non- metabolomics lipidomics platforms we mapping pathway network...
In the era of Big Data, omic-scale technologies, and increasing calls for data sharing, it is generally agreed that use community-developed, open standards critical. Far less upon exactly which should be used, criteria by one choose a standard, or even what constitutes standard. It impossible simply to domain have naturally follow used in all cases. The 'right' often dependent on case scenarios given project. Potential downstream applications data, however, may not always apparent at time...
Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated sources necessary conduct retrospective analytic identify recruit prospective subjects. The Translational Science Award (CTSA) consortium's Informatics IDR Group conducted survey 2010 consortium members evaluate recent trends in implementation use support between 2008 2010. A web-based based part on prior was developed deployed 46...
Abstract Alzheimer’s disease (AD) is a major public health priority with large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) the Neuroimaging Initiative (ADNI) aim to gain new biological insights in We report here an untargeted lipidomics of serum specimens 806 subjects within ADNI1 cohort (188 AD, 392 mild cognitive impairment 226 cognitively normal subjects) along 83 quality control samples. Lipids were detected measured using...
Patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) may require emergency department evaluation hospitalization. Early identification direct preventative supportive care, improving outcomes and reducing health care costs. We developed evaluated a machine learning (ML) approach to predict these events.A total of 8,134 outpatient courses RT CRT from single institution 2013 2016 were identified. Extensive pretreatment data programmatically extracted processed the electronic record...
Machine learning (ML) may cost-effectively direct health care by identifying patients most likely to benefit from preventative interventions avoid negative and expensive outcomes. System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT; NCT04277650) was a single-institution, randomized controlled study in which electronic record-based ML accurately identified at high risk acute (emergency visit or hospitalization) during radiotherapy (RT) targeted them supplemental clinical...
Expert abstraction of acute toxicities is critical in oncology research but labor-intensive and variable. We assessed the accuracy a natural language processing (NLP) pipeline to extract symptoms from clinical notes compared physicians.Two independent reviewers identified present negated National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) v5.0 100 randomly selected on-treatment visits during radiation therapy with adjudication by third reviewer. A NLP based on...
Abstract Autoantigen microarrays are being used increasingly to study autoimmunity. Significant variation has been observed when comparing microarray surfaces, printing methods, and probing conditions. In the present study, 24 surfaces several arraying parameters were analyzed using >500 feature autoantigen printed with quill pins. A small subset of slides, including FAST®, PATH®, SuperEpoxy2, performed well while maintaining sensitivity specificity previously demonstrated by our...
COVID-19 has disproportionately affected non-Hispanic Black or African American (Black) and Hispanic persons in the United States (1,2).In North Carolina during January-September 2020, deaths from were 1.6 times higher among than White (3), rate of cases was 2.3 that (4).During December 14, 2020-April 6, 2021, Department Health Human Services (NCDHHS) monitored proportion persons* aged ≥16 years who received vaccinations, relative to population proportions these groups.On January NCDHHS...
BackgroundDeep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) improve classification accuracy predicting AD using serum-based metabolomics data, specifically lipidomics.MethodsThe c-SWAT methodology builds upon existing Sliding...