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

Resources

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Posters

Poster

High-throughput computational assessment of clinically relevant prostate cancer genetic phenotypes using AI analysis of H&E whole slide images

Oct 2022

Poster

An AI-driven computational biomarker model from H&E slides recovers cases with low levels of HER2 from immunohistochemically HER2-negative breast cancers

Sep 2022

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

Transforming Pathology

Jun 2022

Webinars

Going Digital

May 2022

Case Study

Independent real-world application of Paige Prostate

Oct 2022

Case Study

Paige Breast Lymph Node improves diagnostic accuracy and efficiency

Oct 2022

Case Study

Validation of a digital pathology WSI viewer

Oct 2022

Case Study

An independent assessment of AI for prostate cancer detection

Sep 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

High-throughput computational assessment of clinically relevant prostate cancer genetic phenotypes using AI analysis of H&E whole slide images

An AI-driven computational biomarker model from H&E slides recovers cases with low levels of HER2 from immunohistochemically HER2-negative breast cancers

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

Transforming Pathology

Going Digital

Independent real-world application of Paige Prostate

Paige Breast Lymph Node improves diagnostic accuracy and efficiency

Validation of a digital pathology WSI viewer

An independent assessment of AI for prostate cancer detection

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