The first prototype that applies AI to colorectal diagnosis is developed in Portugal

Portuguese researchers, INESC TEC, and the IMP Diagnostics Molecular & Anatomic Pathology laboratory, focus on improving the prototype that uses AI as a complementary tool when diagnosing colon and rectal biopsies

19 Mar 2024
Jessica Calvey
Product and Reviews Admin Assistant

INESC TEC, and the IMP Diagnostics Molecular & Anatomic Pathology laboratory, worked together to improve the prototype following the availability of the largest database of digital images of colorectal pathologies, with free access for the benefit of research and the advancement of knowledge in this area. The researchers trained this new model using close to 10,000 images of tissues with colorectal pathology, thus achieving a diagnostic acuity of 93.44% and a sensitivity of 99.7% in the detection of high-risk lesions related to this type of cancer. More than half (5300) of the images (close to five terabytes of data) are now available to the scientific community.

The dissemination of digital images is part of the efforts of IMP Diagnostics and INESC TEC to promote science and the sharing of scientific knowledge, following the FAIR principles – a set of international guidelines that recommend that scientific data must be easily findable, accessible, interoperable and reusable.

Pedro Neto, a researcher at INESC TEC, stated, "Part of the images can be used to train other AI models, while the others will be used specifically for testing/benchmarking between AI tools - towards improving thoroughness and fairness when comparing said tools".

The prototype was developed based on a technical innovation, in which a new and more efficient training methodology was applied; it significantly reduces the number of images required to teach the AI model, without compromising its performance. These advances not only drive image analysis technology, but also contribute to the development of more effective solutions in the diagnosis of colorectal cancer.

The paper, 'An interpretable machine learning system for colorectal cancer diagnosis from pathology slides,' published in the journal npj Precision Oncology stems from a collaborative endeavor between both entities, and also features researchers from the Center for Artificial Intelligence in Medicine at the University of Bern, Switzerland.

This work is part of CADPATH.ai, an IMP Diagnostics project partially funded by the COMPETE 2020 programme – which focuses on the development of AI tools for colorectal and cervical pathologies.

Want the latest clinical science news straight to your inbox? Become a SelectScience member for free today>>

Links

Tags

Cellular PathologyCellular Pathology deals with the microscopic analysis of tissue samples and cells. Sample preparation and processing includes fixation, staining, sectioning and slide mounting, using equipment such microtomes and cryostats. In choosing immunohistochemistry and immunocytochemistry kits, consider chromogens, staining method, antibodies, microscopes and imaging.Artificial Intelligence / Machine LearningArtificial intelligence (AI) and machine learning (ML) are transformative technologies used to analyze complex data, identify patterns, and make data-driven predictions across diverse scientific fields. Automate the analysis of large or complex data sets using AI algorithms and leverage machine learning models to improve diagnostics, accelerate drug discovery, and refine experimental design. Discover the best AI/ML software, platforms, and analytical tools in our peer-reviewed product directory: compare features, read customer reviews, and request pricing directly from manufacturers.
The first prototype that applies AI to colorectal diagnosis is developed in Portugal