Lawrence Tarbox

Associate Professor

Last publication 2025 Last refreshed 2026-05-16

faculty

Biomedical Informatics, College of Medicine

LTarbox@uams.edu

12 h-index 30 pubs 5,145 cited

Biography and Research Information

OverviewAI-generated summary

Lawrence Tarbox is an Associate Professor in Biomedical Informatics at the University of Arkansas for Medical Sciences. His research focuses on developing and applying informatics standards and technologies to improve cancer care and medical imaging. He has published on operational ontologies for oncology and radiation oncology, aiming to standardize the use of real-world data for clinical and research purposes. Tarbox's work also includes developing methods for de-identifying medical image datasets and exploring the use of advanced AI models, such as foundation models, for cancer classification. He has investigated guidance for standardization in radiography and the potential for virtual trials in medical imaging innovation. His scholarship metrics include an h-index of 12 with over 5,000 citations across 30 publications. Tarbox collaborates with researchers such as Melody Greer and Jeff Tobler at the University of Arkansas for Medical Sciences.

Metrics

  • h-index: 12
  • Publications: 30
  • Citations: 5,145

Selected Publications

  • Harnessing Native-Resolution 2D Embeddings for Lung Cancer Classification: A Feasibility Study with the RAD-DINO Self-supervised Foundation Model (2025)
  • Toward widespread use of virtual trials in medical imaging innovation and regulatory science (2024)
    13 citations DOI OpenAlex
  • Operational Ontology for Radiation Oncology (OORO): A Professional Society-Based, Multi-Stakeholder Consensus Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data (2023)
  • Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer (2023)
    32 citations DOI OpenAlex
  • AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography (2023)
    6 citations DOI OpenAlex
  • Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile (2023)
  • Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines (2023)
  • Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines (2022)
  • A DICOM dataset for evaluation of medical image de-identification (2021)
    32 citations DOI OpenAlex

View all publications on OpenAlex →

Grants & Funding

  • TO3 TCIA NLST SupportL Radiology/Pathology NIH/Nat. Cancer Institute - Pass Through: Leidos Co-Investigator
  • Pragmatic Randomized Trial of Proton vs. Photon Therapy for Patients with Non-Metastatic Breast Cancer Receiving Comprehensive Nodal Radiation: A Radiotherapy Comparative Effectiveness (RADCOMP) Trial - Continuation Patient-Centered Outcomes Research Institute - Pass Through: Washington University Co-Investigator
  • TCIA Sustainment and Scalability - Platforms for Quantitative Imaging Informatics in Precision Medicine NIH Co-Investigator
  • CDC-NIOSH Chest Image Repository Centers for Disease Control & Prevention - Pass Through: Washington University Principal Investigator
  • NTX XXII Environment & Neurodevelopmental Disorders (CDC) Centers for Disease Control & Prevention Principal Investigator
  • CDC-NIOSH Chest Image Repository Centers for Disease Control & Prevention - Pass Through: Washington University Principal Investigator
  • Robust and Trusted Data Analytics (DART) National Science Foundation - Pass Through: Arkansas Economic Development Commission Co-Investigator
  • Resources for development and validation of Radiomic analyses & Adaptive Therapy NIH Co-Investigator

Collaboration Network

108 Collaborators 49 Institutions 6 Countries

Top Collaborators

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