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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Hospitals and imaging facilities are overwhelmed by the influx of discs from various external sources. The process of manually importing this data proves to be both labor-intensive and expensive. However, with the implementation of the Automated Disc Importer, these organizations can efficiently transfer large quantities of discs into either temporary cloud storage or local systems without requiring human assistance. After the discs are processed, users are able to validate the data before it is officially archived. Additionally, this system enhances security by capturing an image of each disc label during the reading process, which aids in maintaining a comprehensive audit trail. These photographs not only document the imports but also specify the origin of each disc. By leveraging the Automated Disc Importer, medical images and reports from DICOM discs are effectively processed, significantly minimizing the time previously dedicated to manual data entry, and improving overall workflow efficiency. This innovation represents a substantial advancement in the management of medical imaging data.

Description

Qure.ai's qLC-Suite is a cutting-edge AI-driven tool aimed at improving the early identification and management of lung nodules, which is crucial for prompt lung cancer intervention. This solution delivers accurate measurements, thorough characterization, and 3D imaging of lung nodules, ensuring that opportunities for early treatment are not overlooked. It is capable of supporting both incidental and targeted screenings by efficiently identifying nodules and calculating their volume with just one click. Moreover, the system monitors volumetric changes over time, providing valuable insights into nodule development. The qLC-Suite is designed to integrate smoothly into current workflows, offering quick analysis and reporting that assist healthcare professionals in their decision-making processes. In addition to its analytical capabilities, it serves as a comprehensive platform for managing lung nodules, facilitating care coordination through intelligent prompts, providing hardware-agnostic image viewing for AI-enhanced chest X-rays and CT scans, enabling seamless sharing of scans across departments, and allowing for tailored notifications for cases of concern. Overall, qLC-Suite represents a significant advancement in lung cancer care, promoting timely interventions that can ultimately save lives.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)

Integrations

Amazon Web Services (AWS)

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

DatCard Systems

Country

United States

Website

www.datcard.com

Vendor Details

Company Name

Qure.ai

Founded

2016

Country

United States

Website

www.qure.ai/product/lung-nodule-management

Product Features

Medical Imaging

Automated Routing
Comparison View
Compliance Management
Data Import / Export
Diagnostic Reporting
Image Analytics
Treatment Planning
Workflow Management

Radiology

Audit Trail
Billing & Invoicing
Claims Management
EDI
EMR HL7 Bridge
Image Fusion
PACS Integration
Patient Scheduling
Scanning Input
Teleradiology
Wait List Management

Product Features

Medical Imaging

Automated Routing
Comparison View
Compliance Management
Data Import / Export
Diagnostic Reporting
Image Analytics
Treatment Planning
Workflow Management

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