Toby C. Cornish

Toby C. Cornish

Professor of Pathology and Data Science Institute

Medical College of Wisconsin

Froedtert Health

Biography

Toby Cornish completed his M.D. and Ph.D. (Neuroscience) at the University of Illinois and his residency, fellowship, and informatics training at Johns Hopkins. He joined the Johns Hopkins faculty in 2010, where he served as Co-director for Imaging and Image Analysis of the Oncology Tissue Services Lab and developed software packages for biomarker quantitation, including TMAJ/FrIDA, PIP, and HPASubC. In 2016, he was recruited to the University of Colorado, where he served as Vice-Chair for Pathology Informatics and Medical Director of the LIS for the UCHealth system, and was granted tenure in 2023. He is currently a Professor in the Department of Pathology and the Data Science Institute at the Medical College of Wisconsin, where he practices gastrointestinal and pancreaticobiliary pathology and serves as Director of Informatics and Pathology & Laboratory Medicine Informatics Officer at Froedtert Hospital.

His interests include digital pathology, computational pathology, artificial intelligence/machine learning, and histologic image analysis. Dr. Cornish served as President of the Association for Pathology Informatics (2022) and is currently Co-chair of API’s Publications Committee. He previously served on the College of American Pathologists Digital and Computational Pathology Committee and Artificial Intelligence Committee, and was a member of the HIMSS-SIIM Enterprise Imaging Community Advisory Council. He was named to The Pathologist magazine’s Power List 2020 for Big Breakthroughs and currently serves as Senior Associate Editor for Modern Pathology and Associate Editor for Informatics of the American Journal of Clinical Pathology. He is board certified in both Anatomic Pathology and Clinical Informatics.

Download Dr. Cornish’s curriculum vitae.

Interests
  • Clinical Informatics
  • Pathology Informatics
  • Artificial Intelligence
  • Digital Pathology
  • Computational Pathology
  • Histologic and Cytologic Image Analysis
  • Gastrointestinal Pathology
  • Pancreaticobilliary Pathology
  • Pancreatic Neoplasia
Education
  • Clinical Informatics Certificate, 2011

    Johns Hopkins University

  • Gastrointestinal and Liver Pathology Fellow, 2010

    Johns Hopkins University

  • Anatomic Pathology Resident, 2009

    Johns Hopkins University

  • PhD in Neuroscience, 2004

    University of Illinois Urbana Champaign (UIUC)

  • MD, 2005

    University of Illinois Chicago (UIC)

  • BS in Biochemistry, 1995

    Bradley University

Recent & Upcoming Talks

Digital and Computational Pathology in Routine Diagnosis: The Nuts and Bolts of Adoption
This is an exciting time in pathology as pathology is transforming, entering into an era of rapid discoveries and technological advances based on robust advances. Next generation pathology tools, including new technological advances in anatomical pathology, are already being deployed, and many more are rapidly getting developed in research settings. The ongoing technological advances in digital whole slide imaging scanners, image visualization methods, and the integration of artificial intelligence (AI)-derived algorithms into pathology applications are already being used by some pathologists. The benefits of these tools include ease of remote access to cases via the cloud, avoidance of physical storage space, and no risk of deterioration of staining quality or breakage of slides, to name a few. There are advances in genomics, spatiomics, biomarker assessment, multiplexing, and other advanced imaging tools that can now provide single-cell and 3D information to anatomical pathologists. The focus of this course is to provide practical insights into the status of several technological advances in anatomical pathology, such as whole slide imaging, artificial intelligence, augmented reality, genomics, bioinformatics, multiplexing, and advanced imaging tools such as 3D rendering of pathology images. The speakers will provide insights into how close we are today to reaping the benefits of these tools and solutions for routine pathology practice. This course material will allow pathologists to be better prepared to adopt and implement these advances in their daily practice. Expert speakers in these areas will provide an overview of the complexities and barriers of implementing these tools for widespread adoption. Some of the barriers that will be highlighted include cost, technical glitches, interoperability, and, most importantly, professional hesitation to adopt new technology.

Recent Publications

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(2024). Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings. Science Advances.

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(2024). 3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure.. bioRxiv : the preprint server for biology.

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(2023). Learning with limited target data to detect cells in cross-modality images. Medical Image Analysis.

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(2023). Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings. bioRxiv.

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(2023). Three-dimensional assessments are necessary to determine the true spatial tissue composition of diseased tissues. bioRxiv.

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