Built upon landmark research

Paige has received global recognition for advanced research in the field of digital and computational pathology. Our pathologists, AI scientists, engineers, and product specialists have published a number of peer-reviewed journal articles and clinical abstracts.

Latest Publication

Independent real-world application of a clinical-grade automated prostate cancer detection system

Latest Publication

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy

Latest Publication

Validation of a digital pathology system including remote review during the COVID-19 pandemic

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Posters

Poster

An Artificial Intelligence-Based Predictor of CDH1 Biallelic Mutations and Invasive Lobular Carcinoma

Dec 2021

Poster

Subtyping invasive carcinomas and high-risk lesions for machine learning based breast pathology

Dec 2021

Poster

Pathologist-led definition of generalizability and performance metrics for clinical AI ensures patient-relevant performance and clinical usability

Jun 2021

Poster

Pathologist-driven experience drives design of AI-based digital diagnostics

Apr 2021

Publications

Publication

Independent real-world application of a clinical-grade automated prostate cancer detection system

Apr 2021

Publication

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy

Mar 2021

Publication

Validation of a digital pathology system including remote review during the COVID-19 pandemic

Jun 2020

Publication

Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies

May 2020

Publication

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

Jul 2019

Webinars

Understanding the Use of AI in Digital Pathology

Jul 2022

Webinars

Transforming Pathology

Jun 2022

Webinars

Going Digital

May 2022

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Built upon landmark research

Paige has received global recognition for advanced research in the field of digital and computational pathology. Our pathologists, AI scientists, engineers, and product specialists have published a number of peer-reviewed journal articles and clinical abstracts.

Independent real-world application of a clinical-grade automated prostate cancer detection system

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy

Validation of a digital pathology system including remote review during the COVID-19 pandemic

Resources

An Artificial Intelligence-Based Predictor of CDH1 Biallelic Mutations and Invasive Lobular Carcinoma

Subtyping invasive carcinomas and high-risk lesions for machine learning based breast pathology

Pathologist-led definition of generalizability and performance metrics for clinical AI ensures patient-relevant performance and clinical usability

Pathologist-driven experience drives design of AI-based digital diagnostics

Independent real-world application of a clinical-grade automated prostate cancer detection system

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy

Validation of a digital pathology system including remote review during the COVID-19 pandemic

Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

Understanding the Use of AI in Digital Pathology

Transforming Pathology

Going Digital

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