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

Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection

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

Resources

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Posters

Poster

A Deep Learning Artificial Intelligence Algorithm Helps Pathologists Improve Diagnostic Accuracy And Efficiency In The Detection Of Lymph Node Metastases in Breast Cancer Patients

Mar 2023

Poster

Deep learning-based assessment of HER2-low expression on breast cancer H&E digital whole slide images

Dec 2022

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

Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection

Dec 2022

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

Path to Reimbursement for Digital Pathology: Current State and Opportunities

Nov 2022

Webinars

Digital Pathology Assays: Harnessing the power of deep learning from clinical trials to the clinic

Sep 2022

Webinars

Understanding the Use of AI in Digital Pathology

Aug 2022

Webinars

Transforming Pathology

Jun 2022

Webinars

Going Digital

May 2022

Case Study

Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection

May 2023

Case Study

Artificial intelligence–assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies

Mar 2023

Case Study

AI Gleason Grading in the Wild

Jan 2023

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

An independent assessment of AI for prostate cancer detection

Sep 2022

Stay Updated

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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.

Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection

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

Resources

A Deep Learning Artificial Intelligence Algorithm Helps Pathologists Improve Diagnostic Accuracy And Efficiency In The Detection Of Lymph Node Metastases in Breast Cancer Patients

Deep learning-based assessment of HER2-low expression on breast cancer H&E digital whole slide images

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

Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection

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

Path to Reimbursement for Digital Pathology: Current State and Opportunities

Digital Pathology Assays: Harnessing the power of deep learning from clinical trials to the clinic

Understanding the Use of AI in Digital Pathology

Transforming Pathology

Going Digital

Clinical Validation of Artificial Intelligence–Augmented Pathology Diagnosis Demonstrates Significant Gains in Diagnostic Accuracy in Prostate Cancer Detection

Artificial intelligence–assisted cancer diagnosis improves the efficiency of pathologists in prostatic biopsies

AI Gleason Grading in the Wild

Independent real-world application of Paige Prostate

Paige Breast Lymph Node improves diagnostic accuracy and efficiency

An independent assessment of AI for prostate cancer detection

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