Public source

Reviewed 11 May 2026

Completeness Fair (28%)

CS-PDL1 Algorithm by NucleIQ®

Cells IA

The CS-PDL1 algorithm is intended for cancer screening in lung tissue samples: - Detection of cells positive for the PDL1 antibody. - Assists in diagnosing pathological conditions related to the presence of the PDL1 antibody. - Provides specific information about a physiological or pathological state. - A quantitative automated algorithm that integrates Artificial Intelligence. - Uses lung tissue samples from patients of any gender and age. Therefore, the purpose of the algorithm is to provide the pathologist or healthcare professional using it with an automatic identification of findings, facilitating the interpretation of areas with cancer on an image of a processed lung tissue sample. This is achieved by highlighting potential areas of interest so that the pathologist can make a faster and safer diagnosis, less influenced by inter-observer variability since it is standardized. The diagnosis provided by the algorithm is not definitive: it must always be validated by the pathologist, who confirms the accuracy of the generated information.

No papers to support — we monitor for new evidence.

General Information

Product name

CS-PDL1 Algorithm by NucleIQ®

Company

Modality

Histopathology

Main task

Scoring (IHC quantification)

Subspeciality

Pulmonary pathology

Organ/Specimen source

Not specified

Disease targeted

Lung cancer

Specimen type

Not specified

Staining

IHC

Stain subtype

PD-L1

Regulatory Information

CE-IVD Certification

Pathway:

In Vitro Diagnostic Directive (IVDD)

Class:

General IVD Devices

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

Not specified

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

Not specified

Viewer systems

Not specified

Market Presence

On market since

Not specified

AI Platforms

Resellers

Not specified

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: Apr 23, 2026 | Last updated: May 11, 2026