Lawrence Tarbox
Associate Professor
Also affiliated: Boston University (2015); Leidos (United States) (2015); Washington University in St. Louis (2009–2015); University of Utah (1983); LDS Hospital (1996); University of Utah Hospital (1996); Mallinckrodt (United States) (2007–2015); Frederick National Laboratory for Cancer Research (2015); Siemens (United States) (1988–1989)
Faculty Researcher
Biomedical Informatics, College of Medicine
Research Areas
Biomedical Subjects
Links
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: 5,276
Selected Publications
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Harnessing Native-Resolution 2D Embeddings for Lung Cancer Classification: A Feasibility Study with the RAD-DINO Self-supervised Foundation Model (2025)
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Toward widespread use of virtual trials in medical imaging innovation and regulatory science (2024)
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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)
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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)
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AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography (2023)
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Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile (2023)
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Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines (2023)
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Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines (2022)
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A DICOM dataset for evaluation of medical image de-identification (2021)
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PRISM: A Platform for Imaging in Precision Medicine (2020)
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DICOM Images Have Been Hacked! Now What? (2019)
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Summary of the AAPM task group 248 report: Interoperability assessment for the commissioning of medical imaging acquisition systems (2019)
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The public cancer radiology imaging collections of The Cancer Imaging Archive (2017)
Grants & Funding
As listed on this researcher's institutional profile.
- TO3 TCIA NLST SupportL Radiology/Pathology NIH/Nat. Cancer Institute via 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 via 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 via Washington University Principal Investigator
- NTX XXII Environment & Neurodevelopmental Disorders (CDC) Centers for Disease Control & Prevention Principal Investigator
- Robust and Trusted Data Analytics (DART) National Science Foundation via Arkansas Economic Development Commission Co-Investigator
- Resources for development and validation of Radiomic analyses & Adaptive Therapy NIH Co-Investigator
- Tools for data curation, quality control and data interoperability European Commission via Universitat de Barcelona Co-Investigator
- Cancer Center of Nanotechnology Excellence - Continuation - Continuation - Continuation - Continuation NIH/Nat. Cancer Institute via Washington University Co-Investigator
- DART GRA -Ussery year 5 National Science Foundation via Arkansas Economic Development Commission Principal Investigator
- TO4 Moonshot BioBank – Support to IROC NIH/Nat. Cancer Institute via 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 - Continuation Patient-Centered Outcomes Research Institute via Washington University Co-Investigator
- TCIA TO7 Apollo NIH/Nat. Cancer Institute via Leidos Co-Investigator
- Robust and Trusted Data Analytics National Science Foundation via Arkansas Economic Development Commission Co-Investigator
- TCIA Sustainment and Scalability - Platforms for Quantitative Imaging Informatics in Precision Medicine - Year 4 - Continuation NIH/Nat. Cancer Institute Co-Investigator
- EPSCoR - CASE Summer National Science Foundation via Arkansas Economic Development Commission Principal Investigator
- Expanding Translational Research in Arkansas NIH Co-Investigator
Collaboration Network
Top Collaborators
- A DICOM dataset for evaluation of medical image de-identification
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- Harnessing Native-Resolution 2D Embeddings for Lung Cancer Classification: A Feasibility Study with the RAD-DINO Self-supervised Foundation Model
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- Informatics Infrastructure in a Rural Pediatric Clinical Trials Network: Matching Specific Clinical Research Needs with Best Practices and Industry Guidelines
- Informatics infrastructure in a rural pediatric clinical trials network: Matching specific clinical research needs with best practices and industry guidelines
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
- AAPM task group report 305: Guidance for standardization of vendor‐neutral reject analysis in radiography
- Supplemental Material to AAPM Task Group Report 305: Proposed IHE Profile
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