A5101907843- Cell Image Analysis Techniques
- Bioinformatics and Genomic Networks
- Topological and Geometric Data Analysis
- Multiple Sclerosis Research Studies
- Ultrasound Imaging and Elastography
- Diabetes Management and Education
- Mobile Health and mHealth Applications
- Brain Tumor Detection and Classification
- Medical Imaging and Analysis
- Health, Environment, Cognitive Aging
- Functional Brain Connectivity Studies
- Systemic Lupus Erythematosus Research
- Advanced MRI Techniques and Applications
- Primary Care and Health Outcomes
- Artificial Intelligence in Healthcare and Education
- Adversarial Robustness in Machine Learning
- Medical Image Segmentation Techniques
- Rheumatoid Arthritis Research and Therapies
- Immunotoxicology and immune responses
- Advanced Biosensing Techniques and Applications
- Family Support in Illness
- Cardiovascular Health and Risk Factors
- Mobile Learning in Education
- Patient Satisfaction in Healthcare
- Neural Networks and Applications
Sandia National Laboratories California
2024
University of California, Davis
2022-2023
Applied Mathematics (United States)
2023
University of California Davis Medical Center
2023
University of California, Berkeley
2007-2017
University of California, San Francisco
2014-2017
An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods cervical cross-sectional area measurement with an excellent performance close equal manual segmentation. However, still challenging due small size shape, active research being conducted by groups around world this field. Therefore a challenge was organised...
Although multiple HLA alleles associated with sclerosis (MS) risk have been identified, genotype-phenotype studies in the region remain scarce and inconclusive.To investigate whether MS risk-associated also affect disease phenotypes.A cross-sectional, case-control study comprising 652 patients who had comprehensive phenotypic information 455 individuals of European origin serving as controls was conducted at a single academic research site. Patients evaluated Multiple Sclerosis Center...
As deep neural networks (DNNs) become increasingly common, concerns about their robustness do as well. A longstanding problem for deployed DNNs is behavior in the face of unfamiliar inputs; specifically, these models tend to be overconfident and incorrect when encountering out-of-distribution (OOD) examples. In this work, we present a topological approach characterizing OOD examples using latent layer embeddings from DNNs. Our goal identify features, referred landmarks, that indicate We...
To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T1 -weighted scans related to gradient nonlinearity (GNL) and subject positioning; (ii) effect vendor-implemented GNL corrections; (iii) easily applicable methods that can be used retrospectively correct data.A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with same protocol without GNL-distortion correction. Two healthy subjects a phantom were additionally...
Abstract Tissue classification plays a crucial role in the investigation of normal neural development, brain-behavior relationships, and disease mechanisms many psychiatric neurological illnesses. Ensuring accuracy tissue is important for quality research and, particular, translation imaging biomarkers to clinical practice. Assessment with human eye vital correct various errors inherent all currently available segmentation algorithms. Manual assurance becomes methodologically difficult at...
With the recent advancement of mobile technologies, such as smart phones, digital cameras and PDAs (Personal Digital Assistants), tablet PCs learning provides opportunities for formal informal education in a wide range settings. In particular, use technologies to access libraries opens up doors providing unique experiences, both inside outside classroom. This paper presents design implementation library infrastructure test applications. We first conducted user needs analysis students,...
Objective: To estimate spinal cord (SC) gray matter (GM) area’s potential as a biomarker of disease progression in multiple sclerosis (MS), we must understand how early the MS course SC GM atrophy can be detected, which parts are affected, and relationship to SC-relapses T2-lesions. Background: was recently described vivo patients with long-standing shown correlate disability type. Design/Methods: As part an observational cohort study, one hundred seventeen subjects were scanned axial...
<h3>Importance</h3> Primary care is increasingly delivered at or near workplaces, yet utilization and cost of employer-sponsored primary services remain unknown. <h3>Objective</h3> To compare the health an on-site, near-site, virtual comprehensive service delivery model with those traditional community-based care. <h3>Design, Setting, Participants</h3> This population-based cohort study 23 518 commercially insured employees dependents engineering manufacturing firm headquartered in southern...
<h3>Context:</h3> Since many patients with Major Depressive Disorder (MDD) have anhedonia and can be reluctant to engage in treatment, practices struggle depression regular follow up care. The Patient Health Questionnaire-9 (PHQ9) help measure response remission, is the main quality used assess treatment success. <h3>Objective:</h3> Evaluate effectiveness of a PHQ9 outreach via mobile app increase clinical engagement improve care quality. <h3>Study Design:</h3> We created population health...
Introduction: Topological data analysis (TDA) is an emerging mathematical technique that imposes structure on a dataset and examines the shapes (or topological features) arise. The TDA algorithm Mapper Plus proposed to study spatial characteristics of clinical for purpose patient classification. This data-driven hypothesis-free approach risk stratification. Hypothesis: hypothesis can classify distinctive subsets patients receiving optimal treatments post-acute myocardial infarction (AMI)....
Introduction: Atrial fibrillation (AF) represents one of the most common arrhythmias seen clinically and is associated with a significant increase in morbidity mortality, yet, current treatment paradigms have proven largely inadequate. One main contributors to pathophysiology AF inflammation. Hence, reduction inflammation atrial remodeling novel therapeutic strategy for AF. biologically important groups oxylipins (oxygenated lipids) eicosanoids that are potent modulators immune responses...
Background In modern cohorts of MS patients there are a variety treatments that potentially change the disease course. Predicting clinical disability has been difficult and weak correlations found between EDSS MRI measurements. The choice best model from large set clinical, demographic, variables is confounded by non-normal distributions collinearity variables. Conventional approaches including step-wise linear regression known to produce unstable results under these conditions. Objectives...
<h3>CONTEXT:</h3> Ensuring patients with chronic conditions achieve regular follow up is a challenge in primary care. While disease-based algorithms provide guidance for care, many need more individualized care plan recommendations that are delivered through mobile applications. OBJECTIVE: Develop tiered-based outreach system provides follow-up We tested whether these recommendations, mobile-app notification system, increased patient up. <h3>STUDY DESIGN:</h3> developed an algorithm...
<h3>CONTEXT:</h3> Despite the importance of screening, estimates indicate that 12-18% women have not had recent cervical cancer screening and 25-50% are up to date with current guidelines; more than 50% cancers in who screening. Many patients do receive regular preventive care, which often occurs context an annual visit. Patients diabetes need frequent follow-ups prevent complications condition. <h3>OBJECTIVE:</h3> Evaluate effectiveness automated system for outreach examinations, monitoring...
OBJECTIVES/GOALS: The aim of this study is to analyze electronic health record (EHR) data using Mapper PLUS (MP), a new mathematical model, classify acute myocardial infarction (MI) patients by risk major adverse events (AE). We tested MP’s ability define patient subgroups with distinctive for death, heart failure or recurrent MI after revascularization. METHODS/STUDY POPULATION: An EHR retrospective analysis 797 and 29 variables (i.e., laboratory tests, imaging, vitals, clinical traits)...
Background: Elevated troponin levels, a biomarker of myocardial injury (MI), has emerged as predictor acute COVID-19 outcomes. However, lack routine use in most patients makes it difficult to evaluate stand-alone predictor. We aimed combine levels and new rapid, unbiased topological clustering pipeline test for improvements clinical risk stratification during COVID hospitalizations. Methods: SlicerDicer (SD) is an intuitive, anonymous electronic health record (EHR) data exploration tool that...
This study investigates the potential of C2–C3 spinal cord atrophy as an outcome biomarker for clinical trials in multiple sclerosis (MS).