New dataset released for AI-driven colorectal cancer grading

Researchers have introduced CRC-HGD, a new dataset containing 1,914 histopathological images for grading colorectal cancer. The dataset, sourced from Isfahan University of Medical Sciences in Iran, includes images from 214 patients diagnosed between 2014 and 2019. These images are categorized into three differentiation grades (well, moderately, and poorly differentiated) according to World Health Organization criteria and are available at four magnification levels. This resource aims to facilitate the development of AI models for automated cancer grading. AI

IMPACT Enables development of AI models for more accurate and automated grading of colorectal cancer.

RANK_REASON The item describes a new dataset for a specific research area (histopathological image analysis for cancer grading), published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

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• colorectal cancer
• CRC-HGD
• Hamidreza Bolhasani
• Iran
• Isfahan University of Medical Sciences
• Mendeley Data
• Poursina Hakim Research Center
• World Health Organization

• paper
• other

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