A5001424327- Multiple Myeloma Research and Treatments
- Protein Degradation and Inhibitors
- Radiomics and Machine Learning in Medical Imaging
- Cancer Treatment and Pharmacology
- Lung Cancer Treatments and Mutations
- Cancer Mechanisms and Therapy
- Chemokine receptors and signaling
- Peptidase Inhibition and Analysis
- Assistive Technology in Communication and Mobility
- Chronic Lymphocytic Leukemia Research
- Telemedicine and Telehealth Implementation
- Cancer Genomics and Diagnostics
- Monoclonal and Polyclonal Antibodies Research
- Lymphoma Diagnosis and Treatment
- Cancer Immunotherapy and Biomarkers
- Breast Cancer Treatment Studies
- Hearing Loss and Rehabilitation
- Hematopoietic Stem Cell Transplantation
- Advanced Breast Cancer Therapies
- Carcinogens and Genotoxicity Assessment
- AI in cancer detection
- Colorectal Cancer Screening and Detection
- COVID-19 Clinical Research Studies
- Advanced X-ray and CT Imaging
- HIV/AIDS drug development and treatment
University of Arkansas for Medical Sciences
2014-2025
Winthrop Rockefeller Foundation
2024
Erasmus MC Cancer Institute
2019
“Just Accepted” papers have undergone full peer review and been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, proof before it is published its final version. Please note that during production of the copyedited article, errors may be discovered which could affect content. Purpose To construct evaluate performance a machine learning model bone segmentation using whole-body CT images. Materials Methods In this retrospective...
Background The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content BM tissue itself. To address this limitation research, we systematically characterized whole (WBM) during premalignant, baseline, treatment, and post-treatment phases. Methods findings Between 2004 2019, 998 samples...
Abstract As the COVID-19 pandemic unfolds, radiology imaging is playing an increasingly vital role in determining therapeutic options, patient management, and research directions. Publicly available data are essential to drive new into disease etiology, early detection, response therapy. In crisis, National Cancer Institute (NCI) has extended Imaging Archive (TCIA) include related images. Rural populations one population at risk for underrepresentation such public repositories. We have...
Abstract We developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms. objects (a total 1,693 CT, MRI, PET, and digital X-ray images) were selected from datasets published in Cancer Imaging Archive (TCIA). Synthetic Protected Health Information (PHI) was generated inserted into Attributes mimic typical clinical imaging exams. The Standard TCIA curation audit logs guided insertion synthetic PHI standard non-standard data elements. A team tested...
Abstract Introduction: Gait, balance, and cognitive impairment make travel cumbersome for People with Parkinson’s disease (PwPD). About 75% of PwPD cared at the University Arkansas Medical Sciences’ Movement Disorders Clinic reside in medically underserved areas (MUAs). Validated remote evaluations could help improve their access to care. Our goal was explore feasibility telemedicine research visits evaluation multi-modal function a rural state. Methods: In-home were performed PwPD. Motor...
Abstract Background: Impaired motor and cognitive function can make travel cumbersome for People with Parkinson’s disease (PwPD). Over 50% of PwPD cared at the University Arkansas Medical Sciences (UAMS) Movement Disorders Clinic reside over 30 miles from Little Rock. Improving access to clinical care is needed. Objective: To explore feasibility remote clinic-to-clinic telehealth research visits evaluation multi-modal in PwPD. Methods: residing within a UAMS Regional health center were...
8604 Background: Previous research indicated that PC from AMG and CMM could not be distinguished at the GEP level. We reported a GEP70 risk score identify subset of patients high for progression to requiring therapy. now re-address this issue in larger population (pts) order contribute better understanding genetics event clinically benign malignant disease. Methods: identified baseline GEPs 89 pts with 38 MGUS our observational study compared them 785 previously untreated MM who were...
22078 Background: Follicular lymphoma (FL) is an attractive model for discovering biomarkers and elucidating mechanisms of tumor progression. We hypothesized that alterations in the expression proteins with known roles hematological cancers might correlate clinical outcome thereby shed light on biological mechanisms. Methods: Sections from a tissue microarray (TMA) containing FL samples 67 patients were immunostained candidate biomarkers, including p53, p16INK4a, bcl-2, bcl-6, MUM1, p65,...