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What is Volpara Health?

Volpara Health software is employed by numerous facilities, including top cancer screening centers across the United States, to aid in the early identification of breast cancer. Mammography technologists rely on this innovative software to improve the quality of mammograms significantly. Acknowledged as the most scientifically validated tool for screening in the breast health arena, Volpara provides critical evidence at pivotal moments. It grants access to detailed patient information, leading to more precise evaluations of breast cancer risk. Each image processed not only contributes to immediate assessments but also helps refine our algorithms for early disease detection in the long term. Your involvement is vital in advocating for further screening or genetic testing for patients. The platform supports the design of customized worklists and reports tailored to specific preferences. Users can conveniently access statistics and lists through a unified interface, streamlining the workflow. Standardized communication across patients, referrers, and insurers fosters clarity and consistency throughout the process. Additionally, it improves the presentation of result letters by including thumbnail images of mammograms, which enhances the engagement and informativeness of the content. This comprehensive strategy ultimately leads to improved patient care and better outcomes in breast health, paving the way for advancements in the field.

What is Lunit?

Artificial intelligence is essential in the early detection of cancers, enabling timely interventions that can significantly improve survival rates. Given the complexity of cancer, each type possesses unique traits, accompanied by vast amounts of data that necessitate meticulous examination. AI's strength lies in its ability to analyze intricate information, uncovering valuable insights that bolster cancer treatment methodologies. With access to accurate and pertinent data, we can adopt a proactive approach in our fight against cancer. Through the application of AI technologies, we are on the verge of achieving remarkable progress in combating this disease. Our advanced AI systems are capable of detecting early-stage cancer with exceptional precision, boasting detection rates that range from 97% to 99%. They effectively recognize ten of the most common abnormalities in chest x-rays, thereby improving one of the primary diagnostic tools used in medicine. This groundbreaking advancement not only optimizes the radiology process but also reduces the burden on radiologists. Lunit INSIGHT CXR successfully captures a comprehensive array of findings, equipping us to confront the obstacles associated with cancer detection and treatment head-on. As we look ahead, the integration of AI into cancer care heralds a future filled with hope and innovative solutions. The continuous evolution of these technologies promises to redefine our approach to healthcare and improve patient outcomes significantly.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Volpara Health

Date Founded

2009

Company Location

New Zealand

Company Website

www.volparahealth.com

Company Facts

Organization Name

Lunit

Company Location

United States

Company Website

www.lunit.io/en

Categories and Features

Categories and Features

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