Enter the era of spatial biology. Make tissue environment interpretable by getting a better visualization of the biomarker landscape. With the Keen Eye Platform, you can easily visualize cell phenotypes within segmented area on whole tissue sections. Gain the capability to fully explore panels of biomarkers specific to your research project.
Keen Eye AI technology allows you to infer high-level labels such as clinical outcomes or global pathology grading, with highly detailed patterns from tissue slides. Through the Platform, access the capabilities of interpretation you need to mine data objectively and efficiently.
At Keen Eye, we have mastered the process of disseminating AI models within global organisations. With the Platform SDK (Software Development Kit), get access to an easy way of deploying your AI models instantaneously within your organisation. No matter the language or AI framework you use, distribute as many AI models as you require.
By Charlotte Plestant (Scientific Content Marketing Manager), Eunice Stennett (Former CMO), David Guet (Digital pathology Specialist) - 26 May 2021
Over the last years, the world of Pathology has considerably evolved and brought out new challenges. Development of whole-slide scanners alongside Artificial Intelligence (AI) has empowered pathological analysis by digitizing immunohistochemistry, immunocytochemistry and H&E slides, providing better possibilities in patient selection and treatment. These changes have come with new hurdles, related to a sharp increase of the complexity of the images, higher expectations for image analysis and a shift in the pathologist's daily practices.
By David Guet, Thomas Le Meur - 05 Feb 2021
For years now, digital pathology has seen the emergence of a plethora of heterogeneous different image types designed for clinical research use or routine diagnostics. Among them one can find tissue microarrays, or TMAs, introduced in the 1990s. TMA images differ from standard histopathological samples; instead of having a whole tissue section on a single slide, we find a large number of tissue cores organized on a grid, from different patients and, possibly from different tissue types. On one TMA slide, we can find several hundred samples.
01 May 2020
At the forefront of AI research in medicine are diagnostics and drug development. Deep learning technology allows better decision making, improved efficiency in clinical trials, and a clearer path to drug development.
By David Guet (Digital Pathology Specialist), Melanie Lubrano (Data Scientist) - 30 Mar 2021
Histopathology is the analysis of tissue samples under a microscope in order to establish the severity of a disease. More precisely, it concerns the examination of tissue extracted from surgery, biopsy or autopsy. The tissue extracted from the body of the patient is placed in a fixative medium in order to prevent decay. It is then embedded in a cassette in wax before being sliced in thin microtome sections. Thin tissue sections are stained using different staining protocols (H&E, chromogenic, immunofluorescence, etc.) and mounted on glass slides before observation.
01 Jul 2020
Many pharmaceutical companies develop their AI capabilities to improve operational efficiencies, scientific research, and the clinical trial process. As for medical image analysis, the complexity and heavy investment of time and effort lead them to turn to specialized partners who possess this expertise. Keen Eye holds a prominent position in this field with significant knowledge inAI, deep learning, and evaluation of large sets of histopathological, diagnostic and molecular images.