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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

AI plays a crucial role in identifying early-stage cancers, facilitating prompt interventions that enhance survival prospects. Cancer's intricate nature means that each type carries distinct characteristics, packed with extensive data that requires thorough analysis. This is where AI excels, leveraging its capabilities to process complex information, ultimately revealing insights that can significantly aid in cancer treatment strategies. Equipped with precise and relevant data, we take proactive steps in our battle against cancer. By utilizing AI, we are poised to make substantial strides in overcoming this disease. Our AI technology is designed to detect early-stage cancer with remarkable accuracy, achieving detection rates between 97-99%. It proficiently identifies ten of the most prevalent abnormalities found in chest x-rays, thus enhancing one of the most fundamental diagnostic tools. This innovation not only streamlines the radiology workflow but also alleviates the workload for radiologists. Lunit INSIGHT CXR successfully encompasses a wide range of findings, ensuring that we are prepared to tackle the challenges presented by cancer detection and treatment. The future of cancer care looks promising with AI at the forefront of these advancements.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS) No 

Integrations

Amazon Web Services (AWS) Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Lunit

Country

United States

Website

www.lunit.io/en

Vendor Details

Company Name

Qure.ai

Founded

2016

Country

United States

Website

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

Product Features

Product Features

Medical Imaging

Automated Routing No 
Comparison View No 
Compliance Management No 
Data Import / Export No 
Diagnostic Reporting No 
Image Analytics No 
Treatment Planning No 
Workflow Management No 

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