Publications

• Article

  Brundage D. A systematic audit of transparency and validation disclosure in commercial veterinary artificial intelligence. Front Vet Sci. 2026;13:1761038. doi:10.3389/fvets.2026.1761038

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• Preprint

  Brundage D. Synthetic Data for Veterinary EHR De-identification: Benefits, Limits, and Safety Trade-offs Under Fixed Compute. arXiv. Published January 13, 2026. doi:10.48550/arXiv.2601.09756

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• Article

  Clunie DA, Flanders A, Taylor A, et al. Report of the Medical Image De-Identification (MIDI) Task Group--Best Practices and Recommendations. Arxiv. 2025;arXiv-2303.

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• Preprint

  Clunie DA, Flanders A, Taylor A, et al. Report of the Medical Image De-Identification (MIDI) Task Group-Best Practices and Recommendations [preprint]. arXiv. 2023.

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• Article

  Rosenthal J, Carelli R, Omar M, et al. Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology. Mol Cancer Res. 2022;20(2):202-206.

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• Article

  Velu P, Cong L, Rand S, et al. Rapid detection of SARS-CoV-2 variants of concern by single nucleotide polymorphism genotyping using TaqMan assays. Diagn Microbiol Infect Dis. 2022;104(4):115789.

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• Preprint

  Brundage D, Rosenthal J, Carelli R, et al. Whole Slide Image to DICOM Conversion as Event-Driven Cloud Infrastructure [preprint]. arXiv. 2022;arXiv:2203.13888.

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• Conference

  Omar M, Xu Z, Carelli R, et al. Using attention-based deep multiple instance learning to identify key genetic alterations in prostate cancer from whole slide images. Cancer Res. 2022;82(12 Suppl):462-462.

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• Conference

  Xu Z, Benedetti E, Carelli R, et al. A multi-omics signature for patients' risk classification in prostate cancer. Cancer Res. 2022;82(12 Suppl):5858-5858.

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• Thesis

  Brundage DM. Prevalence and evaluation of potential abbreviations in intensive care documentation [dissertation]. Rutgers University-School of Health Professions; 2020.

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