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Key Features

  • Atelectasis
  • Consolidation
  • Identifying and highlighting findings
  • Measuring distance tracheal tube and carina
  • Notification with an alert
  • Pleural effusion
  • Pneumothorax
  • Pulmonary lesions

General Information

Product name

AI-Rad Companion Chest X-ray

Subspeciality

Chest

Modality

X-ray

Disease targeted

Pulmonary lesions, pleural effusion, pneumothorax, consolidation, atelectasis, diseases or clinical condition which requires ventilation

Main task

Not specified

Technical Specifications

Population

All upright chest X-rays (PA view) and bedside thorax (AP)

Patient population age

Not specified

Input

Chest/Thorax X-ray, Viewing position: posterior-anterior an anterior-posterior (for limited findings)

Input format

DICOM

Output

Image annotations, Report table of suspected findings with AI confidence score

Output format

DICOM GSPS, DICOM SC, DICOM SR (TID 5000 format)

Integration

Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased

Deployment

Hybrid solution

Trigger for analysis

Automatically, Etc., Image upload, On demand, Right after the image acquisition, Triggered by a user through e.g. a button click

Processing time

1 - 10 minutes

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIb

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

09-2020

AI Platforms

Siemens Healthineers

Resellers

Not specified

Countries present

Not specified

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction

Peer-Reviewed

View

Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion

Peer-Reviewed

View

Evaluation of the clinical performance of an AI-based application for the automated analysis of chest X-rays

Source: vendor | First published: Jun 30, 2024 | Last updated: Jul 10, 2025