Funding Sources

Our research is funded by several grants, including:

  • R01CA276301
    An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.
  • R01DC020715
    Computer-assisted diagnosis of ear pathologies by combining digital otoscopy with complementary data using machine learning.
  • R21 CA273665
    Efficient and cost-effective breast cancer risk stratification using whole slide histopathology images.
  • R21 EB029493
    Development of quantitative tools to predict patients with difficult intubation to minimize treatment-related complications.
  • Alliance Clinical Trials in Oncology
    Automatic detection of tumor buds in colorectal cancer patients from H&E images.
  • R01 1R01HL177046-01
    Incorporating donor lung CT images into machine learning models to predict severe primary graft dysfunction after lung transplantation.
  • Pelotonia IRP Grant 2025
    Leveraging AI and digital pathology to guide precision therapy for metastatic hormone receptor-positive, HER2-negative breast cancer.

Supporting Institutions

  • Comprehensive Cancer Center, The Ohio State University
  • Department of Pathology, The Ohio State University
  • Pelotonia