Public source

Reviewed 10 Oct 2026

Completeness Good (42%)

DiaKwant™ ER/PR

DiaDeep

The DiaKwant™ ER/PR algorithm assists pathologists in evaluating hormonal and proliferative biomarkers.

"DiaKwant™ ER/PR automatically detects invasive tumor regions and performs nuclear-level analysis on IHC slides. DiaKwant™ algorithm quantifies staining intensity and percentage of positive tumor nuclei, providing interpretable whole-slide scores."(https://www.diadeep.com/diakwant)

The DiaKwant™ consists of several algorithms that are a part of a single CE-IVD validated solution.

No papers to support — we monitor for new evidence.

General Information

Product name

DiaKwant™ ER/PR

Company

Modality

Histopathology

Main task

Scoring (IHC quantification)

Subspeciality

Breast

Organ/Specimen source

Breast

Disease targeted

Breast Cancer

Specimen type

Not specified

Staining

IHC

Stain subtype

ER, PR

Regulatory Information

CE-IVD Certification

Pathway:

In Vitro Diagnostic Regulation (IVDR)

Class:

Class C

Not verified by Health AI Register

Scanner Brands Certified for Use (CE-IVD)

Not specified

Scanner Models Certified for Use (CE-IVD)

Not specified

Other certifications

Not specified

Evidence & Research

No research papers or evidence on file yet.

The registry monitors publications for new evidence.

Technical Specifications

Patient population age

Not specified

Input

whole slide image

Input format

Not specified

Output

Not specified

Output format

Not specified

Integration

Not specified

Deployment

Not specified

Trigger for analysis

Not specified

Processing time

Not specified

Population

The DiaKwant™ ER/PR algorithm assists pathologists in evaluating hormonal and proliferative biomarkers in breast cancer.

Viewer systems

Not specified

Market Presence

On market since

April 2026

AI Platforms

Roche Navify, Sectra

Resellers

Sectra

Countries present

Not specified

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Not specified

Based on

Not specified

Source: Public | First published: Oct 10, 2026 | Last updated: Oct 10, 2026